EXPRESSION AND ROLE OF FIBROBLAST GROWTH
FACTOR 9 (FGF9) IN BOVINE FOLLICULOGENESIS
By
LUÍS FERNANDO SCHÜTZ Doctor of Veterinary Medicine Federal University of Rio Grande do Sul Porto Alegre, Brazil 2007
Master of Science in Animal Science Santa Catarina State University Lages, Brazil
Submitted to the Faculty of the Graduate College of the Oklahoma State University in partial fulfillment of the requirements for the Degree of DOCTOR OF PHILOSOPHY July, 2016 EXPRESSION AND ROLE OF FIBROBLAST GROWTH
FACTOR 9 (FGF9) IN BOVINE FOLLICULOGENESIS
Dissertation Approved:
Dr. Leon J. Spicer
Dissertation Adviser
Dr. Robert Wettemann
Dr. Glenn Zhang
Dr. Peter Hoyt
ii
ACKNOWLEDGEMENTS
To my beloved wife, for her love, support, encouragement, and understanding. She made all the steps of the arduous pathway to achieve this degree much easier. With her by my side, I feel much stronger.
To my family in Brazil: my beloved parents, my brother, Lipe, and my sister, Ane, for their love, faith, and support. And to my beautiful niece, Sofia, my sister-in-law, Manuela, and my brother-in-law, Joni.
To my advisor and mentor, Dr. Leon Spicer, for accepting me as a student, for giving me priceless lessons and advice whenever I needed, for stimulating me to develop a critical thinking, and for teaching me how to perform sound science in the field of ovarian folliculogenesis. And to his family, Michael, Melissa, Anna, and Richie, for their friendship and support.
To the Franceschi family: my mother-in-law, Pierina, and my father-in-law, Adi, for their support and encouragement; to my brother-in-law, Junior, his wife, Janine, and his great boys, Bernardo and Bruno; and to my sister-in-law, Sheila, and her fiancé, Fábio.
To my committee members, Dr. Robert Wettemann, Dr. Peter Hoyt, and Dr. Glenn
Zhang for their teaching and support.
To the Faculty of Animal Science Department at OSU, specially Dr. Clint Rusk, Dr.
Jennifer Hernandez-Gifford, and Dr. Craig Gifford, who always have been very supportive.
To all my friends in Brazil, who always encourage me and make my life happier just because I know they will always be there for me.
To the friends and colleagues I met in OSU, especially Marco Albonico, Lingna
Zhang, Britt Boehmer, Bahaa Aloqaily, Pauline Aad, Breanne Morell, Belinda and Renee
iii Acknowledgements reflect the views of the author and are not endorsed by committee members or Oklahoma State University.
Gomez, Cheyenne Robinson, Maria Chiara Perego, Denise Tsuzukibashi, Morgan Totty,
Patrick Jones, Phillip Gunter, and Kyle McLean. Their friendship and support surely made my work and my life in America much more pleasant.
To the Brazilian friends that I have met in Stillwater, especially Rolf and Bia, Tony and Thaís, Samuel and Tathiane, among many others.
To my friends and advisors, Dr. Marcelo Bertolini and Dr. Valério Portela, for their support and encouragement.
To my grandparents, who are no longer with me on earth, but from whom I carry not just my genetic and epigenetic heritage, but everlasting love.
To God, who has always blessed my life, providing me opportunities to meet great people wherever I go.
iv Acknowledgements reflect the views of the author and are not endorsed by committee members or Oklahoma State University.
Name: LUÍS FERNANDO SCHÜTZ
Date of Degree: JULY, 2016
Title of Study: EXPRESSION AND ROLE OF FIBROBLAST GROWTH FACTOR
9 (FGF9) IN BOVINE FOLLICULOGENESIS
Major Field: ANIMAL SCIENCE
Abstract: In the ovaries, many members of the FGF family are involved in the regulation of folliculogenesis. One of these members, FGF9, has been characterized as an anti-differentiation factor for its effects on steroidogenesis of granulosa (GC) and theca cells (TC) of cattle, but whether endogenous production of FGF9 changes during follicular development of cattle was unknown. Also, in order to have a comprehensive view of how FGFs regulate folliculogenesis, information of how endogenous production of their receptors (FGFRs) is also required. The first objectives of our studies presented herein was to characterize FGF9, FGFR1c, FGFR2c, FGFR3c, and FGFR4 mRNA abundance in GC and TC during development of dominant follicles in dairy cattle. Estrous cycles of non-lactating dairy cattle were synchronized, and ovaries were collected on either day 3-4 (n = 8) or day 5-6 (n = 8) post-ovulation for GC and TC mRNA extraction from small (1-5 mm), medium (5.1-8 mm) or large (8.1-18 mm) follicles for PCR analysis. In GC, FGF9, FGFR1c, FGFR2c, and FGFR3c mRNA abundance was greater (P < 0.05) in estrogen (E2)- inactive (i.e., concentrations of E2 < progesterone, P4) follicles than in large E2- active (i.e., concentrations of E2 > P4) follicles. In TC, FGF9 mRNA abundance was greater (P < 0.05) in large E2-inactive follicles than in large E2-active follicles on day 3-4 post-ovulation whereas medium E2-inactive follicles have greater (P < 0.05) FGFR1c and FGFR4 mRNA abundance than large E2-active and E2–inactive follicles on day 5-6 post-ovulation. In addition, FGFR1c, FGFR2c, FGFR3c, and FGFR4 mRNA abundance was greater (P < 0.05) in medium E2-inactive follicles on day 5-6 post-ovulation than on day 3-4 post-ovulation. Following, we aimed to investigate effects of FGF9 on TC through the use of microarray (Affymetrix GeneChip Bovine Genome Arrays) and the bioinformatic tool Ingenuity Pathway Analysis. This software identified differentially expressed transcripts in 346 pathways in response to FGF9 in TC involved in functions such as cell cycle, proliferation, survival, and steroidogenesis. Taken together, these studies reinforce the importance of FGFs in folliculogenesis of cattle.
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TABLE OF CONTENTS
Chapter Page
I. INTRODUCTION ...... 1
II. REVIEW OF LITERATURE ...... 4
1. Fibroblast growth factors family of proteins and their receptors ...... 4 2. Role of fibroblast growth factors on ovarian physiology ...... 7 2.1. Role of fibroblast growth factors and gonadotropins on ovarian steroidogenesis ...... 10 2.2. Role of fibroblast growth factors in proliferation of granulosa and theca cells...... 13 2.3. Role of fibroblast growth factors in ovarian follicular fate ...... 15 2.4. Role of fibroblast growth factors in luteal function ...... 17 2.5. Role of fibroblast growth factor receptors on ovarian physiology ...... 18 3. Role of other growth factors on ovarian physiology ...... 21 3.1. IGF system ...... 22 3.2. Transforming growth factor β family ...... 27 3.2.1. Role of TGF-α and TGF-β on folliculogenesis ...... 28 3.2.2. Role of activin, inhibin, and follistatin on folliculogenesis ...... 29 3.2.3. Role of oocyte-derived GDF-9, BMP-6, and BMP-15 on folliculogenesis ...... 31 3.2.4. Role of BMPs on folliculogenesis ...... 33 3.2.5. Role of AMH on folliculogenesis ...... 34 4. Bioinformatics tools for microarray analysis ...... 35 5. References ...... 41
III. CHANGES IN FIBROBLAST GROWTH FACTOR 9 (FGF9) mRNA IN GRANULOSA AND THECA CELLS DURING OVARIAN FOLLICULAR GROWTH IN DAIRY CATTLE ...... 91
1. Abstract ...... 91 2. Introduction ...... 92 3. Material and methods ...... 93 Animals and Experimental Designs ...... 93 Cell and Follicular Fluid Collection ...... 94 RNA Extraction and Qualitative PCR (qPCR) ...... 94 Radioimmunoassays (RIA) and IGF1 ELISA ...... 95 FGF9 Western Blotting ...... 96 vi
Statistical Analyses ...... 97 4. Results ...... 98 GC FGF9 mRNA Abundance ...... 98 TC FGF9 mRNA Abundance ...... 98 Follicle Size, E2, P4, and Free IGF1 Concentrations in Follicular Fluid ...... 99
vi
Correlations between FFL Concentrations of Hormones and FGF9 mRNA Relative Abundance ...... 100 FGF9 Protein in FFL ...... 100 5. Discussion ...... 100 6. References ...... 113
IV. CHANGES IN FIBROBLAST GROWTH FACTOR RECEPTORS-1c, -2c, -3c, AND -4 mRNA DURING OVARIAN FOLLICULAR GROWTH IN CATTLE ………..119
1. Abstract ...... 119 2. Introduction ...... 120 3. Material and Methods ...... 122 Animals and Experimental Design ...... 122 Cell and Follicular Fluid Collection ...... 123 RNA Extraction and Quantitative PCR (qPCR) ...... 123 Radioimmunoassays (RIA) ...... 124 Statistical Analyses ...... 124 4. Results ...... 125 Size, E2, and P4 Concentrations in Follicular Fluid ...... 125 GC FGFR1c mRNA Relative Abundance ...... 126 GC FGFR2c mRNA Relative Abundance ...... 126 GC FGFR3c mRNA Relative Abundance ...... 126 GC FGFR4 mRNA Relative Abundance ...... 126 TC FGFR1c mRNA Relative Abundance ...... 127 TC FGFR2c mRNA Relative Abundance ...... 127 TC FGFR3c mRNA Relative Abundance ...... 127 TC FGFR4 mRNA Relative Abundance ...... 128 Correlations among Follicular Size, FFL Levels of Steroids, and FGFRs mRNA Relative Abundance ...... 128 5. Discussion ...... 129 6. References ...... 138
V. TRANSCRIPTOME PROFILING OF BOVINE THECA CELLS TREATED WITH FIBROBLAST GROWTH FACTOR 9 ...... 144
1. Abstract ...... 144 2. Introduction ...... 145 3. Material and Methods ...... 147 Reagents and Hormones ...... 147 Cell Collection and In Vitro Culture ...... 148 RNA Extraction, and Microarray and Statistical Analyses ...... 148 Microarray Functional Data Analyses ...... 149 4. Results ...... 149 Identification of Molecular Canonical Pathways Altered by FGF9 Treatment……...... 149 vii
Identification of Biological Functions Altered by FGF9 Treatment ...... 149 Identification of Molecular Networks Affected by FGF9 treatment ...... 150 5. Discussion ...... 151 6. References ...... 164
VI. SUMMARY AND CONCLUSION ...... 173
viii
LIST OF TABLES
Table Page
1. Characterization of FGFs subfamilies and their secretion from cells ...... 39 2. Receptor affinities for different FGFs subfamilies ...... 40 3. Information about primers and probes ...... 133 4. 20 most up-regulated genes by FGF9 treatment in bovine TC ...... 156 5. 20 most down-regulated genes by FGF9 treatment in bovine TC ...... 157
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LIST OF FIGURES
Figure Page
1. Abundance of FGF9 mRNA in granulosa and theca cells during follicular growth ...105 2. Correlation between FGF9 mRNA abundance in granulosa cells and concentrations of E2 in follicular fluid (FFL) ...... 107 3. Effects of follicular size (Lg = Large; Sm = Small) and E2 status (EA = estrogen active; EI = estrogen inactive) on concentrations of free IGF1 ...... 109 4. Results from Western blotting to detect FGF9 protein in FFL ...... 110 5. Schematic model summarizing the hormonal regulation of FGF9 production by granulosa and theca cells ...... 111 6. Effects of follicular size (Lg = Large; Md = Medium; Sm = Small) and E2 status (EA = estrogen active; EI = estrogen inactive) on FGFR1c, FGFR2c, FGFR3c, and FGFR4 mRNA relative abundance in bovine granulosa cells ...... 134 7. Effects of follicular size (Lg = Large; Md = Medium; Sm = Small) and E2 status (EA = estrogen active; EI = estrogen inactive) on FGF1c, FGFR2c, FGFR3c, and FGFR4 mRNA relative abundance in bovine granulosa cells on different days post-ovulation ...... 136 8. Top 10 canonical pathways altered by FGF9 in bovine TC identified by IPA ...... 158 9. Top 10 biological functions for the differentially expressed transcripts altered by FGF9 treatment in bovine TC identified by IPA ...... 159 10. Biological functions related to cell fate altered by FGF9 in bovine TC identified by IPA. Among these functions, based on activation z-score, only proliferation of cell and cell survival were predicted to be significantly increased in response to FGF9 in TC. The numbers on the top of each bar indicate the number of differentially expressed transcripts in each pathway ...... 160 11. Top 10 networks generated by IPA according to score. The greater the area in the graph, the higher the score of the network ...... 161 12. Network of differentially expressed transcripts related to cellular growth and proliferation (Network 3)...... 162 13. Network of differentially expressed transcripts related to steroidogenesis (Network 15: Lipid metabolism, molecular transport, small molecule biochemistry)...... 163
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CHAPTER I
INTRODUCTION
Fibroblast growth factors (FGFs) are polypeptides described to elicit a great variety of actions throughout the system of mammals during embryo development and adult life, including organogenesis, sex determination (Kim et al., 2006), angiogenesis (Cross and
Claesson-Welsh, 2001; Robinson et al., 2008), and wound healing (Zheng et al., 2014). Also, aberrant FGF signaling has been associated with cancer. In fact, the involvement of FGF signaling in cancer incidence has been extensively studied in the last decades, showing the importance of these mitogens for health (Ornitz and Itoh, 2001; Gotoh, 2008; Nakao et al.,
2013; Tanner and Grose, 2016). Moreover, there is an increasing body of studies throwing light on the functions of FGFs in the reproduction.
Currently, out of the 22 members of the mammalian FGF family, ten have been reported to be synthesized at different degrees in the oocyte, theca cells (TC), and granulosa cells (GC), playing autocrine, paracrine, and endocrine roles in the ovary (Drummond et al.,
2007; Machado et al., 2009; Portela et al., 2010; Schreiber and Spicer, 2012; Castilho et al.,
2015; Ferreira et al., 2016). These roles include regulation of steroidogenesis (Baird and
Hsueh, 1986; Vernon and Spicer, 1994; Schreiber and Spicer, 2012), cell proliferation
(Gospodarowicz et al., 1977a; Parrott et al., 1994; Spicer and Stewart, 1996; Schreiber et al.,
2012), corpus luteum formation (Gospodarowicz et al., 1977b; Grazul-Bilska et al., 1995;
Robinson et al., 2008), and atresia (Portela et al., 2015).
Among FGFs that regulate folliculogenesis of cattle, FGF9 stimulates GC proliferation while suppressing hormone-stimulated estradiol production (Schreiber and
Spicer, 2012). Because estradiol production is critical for GC survival and differentiation of
1
dominant follicles (Knecht et al., 1985; Fortune et al., 2004), FGF9 appears to have an anti- differentiation function during ovarian follicular development of cattle. Whether endogenous production of FGF9 by ovarian follicular cells change during ovarian follicular growth and selection of cattle remains to be determined. Because FGF9 stimulates bovine TC proliferation while inhibiting steroidogenesis (Schreiber et al., 2012), studies to investigate
FGF9 signaling mechanisms in TC of cattle are of great value for the understanding of how
FGFs affect folliculogenesis in mono-ovulatory species. Advances in biotechnology and bioinformatics tools achieved in the last decades, such as the technology of cDNA microarray, which allows simultaneous measurement of thousands of gene transcripts
(Schena et al., 1995), are critical for such an investigation. Nevertheless, interpretation of data generated by this tool is complex (Bowtell, 1999; Huang et al., 2009; Henderson-MacLennan et al., 2010) and would not be possible without the use of modern bioinformatics tools
(Subramanian et al., 2005; Capriotti et al., 2012). Therefore, advances in bioinformatics technology for microarray-based genomic profiling provide an inestimable contribution to the advance in understanding the roles of various factors in reproductive biology.
To elicit their intracellular actions, FGFs must bind to high affinity single chain transmembrane tyrosine kinase receptors (FGFRs), which have different ligand-specificities and are encoded by four different genes in vertebrates (Itoh and Ornitz, 2004; Ornitz and Itoh,
2015): FGFR1, FGFR2, FGFR3, and FGFR4. The diversity of these receptors is further increased by the occurrence of alternative mRNA splicing of the sequence of the immunoglobulin domain III of the genes FGFR1, FGFR2, and FGFR3, resulting in isoforms
IIIb and IIIc, which are important for determining ligand-binding specificity (Givol and
Yayon, 1992; Ornitz and Itoh, 2001; Itoh and Ornitz, 2004; Li et al., 2016). Due to the different ligand-binding specificities (Ornitz and Itoh, 2015), the localization of FGFRs in the different follicle compartments is of critical importance for the FGFs to exert their effects on ovarian physiology. Indeed, there is variation in the presence of isoforms of FGFRs in GC,
TC, and oocytes (Berisha et al., 2004; Buratini et al., 2007; Machado et al., 2009; Zhang and
2
Ealy, 2012), contributing to the variation in effects of different FGFs observed in folliculogenesis of mammals. Some FGFRs change according to follicular fate (Berisha et al.,
2004; Buratini et al., 2005a; Castilho et al., 2015), adding complexity to the roles of FGFs in ovarian follicular development. Therefore, studies about how endogenous production of some
FGFRs by ovarian follicular cells change during selection of dominant follicles in a monotocous species such as cattle are very much needed for a comprehensive understanding of the roles of FGFs in folliculogenesis.
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CHAPTER II
REVIEW OF LITERATURE
1. Fibroblast growth factors family of proteins and their receptors
Fibroblast growth factors (FGFs) constitute a large family of single chain polypeptide growth factors present in both vertebrates and invertebrates (Ornitz and Itoh, 2001; Dailey et al., 2005; Itoh and Ornitz, 2011; Li et al., 2016). The first members to be reported, FGF1 and
FGF2, were designated acidic and basic FGF in view of their activity to stimulate fibroblast proliferation and their isoelectric point (Armelin, 1973; Gospodarowicz, 1974; Gambarini and
Armelin, 1982). To date, 22 different members of the FGF family have been described in mammals (FGF 1-23, with no FGF15 identified in humans, and no FGF19 identified in rats and mice), most of them sharing highly conserved amino acid residues (Ornitz and Itoh, 2001;
Itoh and Ornitz, 2011). These members can be categorized into several subgroups or subfamilies according to increased similarity in sequence, patterns of expression, function, and developmental and biochemical features, although each FGF still appears to have particular sites of expression (Ornitz and Itoh, 2001).
Currently, mammalian FGFs are classified into seven subfamilies containing two to four members each (Itoh and Ornitz, 2011; Li et al., 2016), as summarized in Table 1. These subfamilies can also be categorized into two general groups: the canonical FGFs, which comprise most of the members, and the non-canonical FGFs, which comprise members 11 to
14 (as reviewed by Li et al., 2016). The canonical FGFs exert autocrine, paracrine, and endocrine actions upon binding to high affinity FGF receptors (FGFRs) whereas the non-
4
canonical FGFs do not bind to FGFRs and act intracellularly through interaction with calcium and voltage-gated sodium channels (Wang et al., 2011; Hennessey e al., 2013; Li et al., 2016).
The majority of FGFs have an N-terminal signal peptide (Table 1) that facilitates secretion from cells through classical mechanisms (Ornitz & Itoh, 2001; Li et al., 2016). A second group of FGFs, including FGF1 (Prudovsky et al., 2003), FGF2 (Abraham et al.,
1986; La Venuta et al., 2015; Steringer et al., 2015), FGF9 (Miyamoto et al., 1993; Miyakawa et al., 1999), FGF16 (Miyake et al., 1998), and FGF20 (Ohmachi et al., 2000), lacks a cleavable signal peptide and its members are secreted in a non-conventional manner, including through membrane pores, independently of the endoplasmic reticulum-Golgi pathway (for reviews, see Ornitz & Itoh, 2001; Li et al., 2016). Finally, a third group of FGFs
(FGF 11 to FGF 14) lacks signal sequences and is believed to remain inside the cell (as reviewed by Ornitz and Itoh, 2001).
As mentioned, FGFs were first reported to promote fibroblast proliferation (Armelin,
1973; Gospodarowicz, 1974), but the functions of these polypeptides go much beyond of what the name implies. In fact, the name nowadays could be considered misleading, given that not all FGFs elicit activity in fibroblasts (Rubin et al., 1989; Powers et al., 2000; Li et al.,
2016). FGFs have been detected in various tissues, playing several roles in development and metabolism, with some members acting exclusively during embryogenesis and others acting in both embryonic and adult tissues (Ornitz and Itoh, 2001). These growth factors can act to stimulate cell steroidogenesis (Johnson et al., 1980), proliferation (Gospodarowicz et al.,
1977a; Murphy et al., 1990), survival (Gospodarowicz and Bialecki, 1978; Sievers et al.,
1987), differentiation (Stemple et al., 1988; Dailey et al., 2005), and migration (Montesano et al., 1986), but they can also prevent cell proliferation (Oesterle et al., 2000) and inhibit differentiation (Joannes et al., 2016). Interestingly, the action of FGFs vary not just according to the cell type, but also to cell cycle stage, with different responses observed in immature and differentiating osteoblasts (Mansukhani et al., 2000).
5
The wide range of the functions of FGFs is influenced by the diversity of high affinity FGFRs and cofactors that regulate the FGF signaling complex. To date, four (FGFR1-
FGFR4) receptors and several cofactors, including heparan sulfates (HS) and Klotho coreceptors have been identified (Givol and Yayon, 1992; Itoh and Ornitz, 2004; Dailey et al., 2005; Li et al., 2016). The FGFRs are tyrosine kinase receptors that have different ligand- specificities (table 2) and are encoded by four different genes in vertebrates (Itoh and Ornitz,
2004; Ornitz and Itoh, 2015). The extracellular ligand-binding portion of FGF receptors contains two or three immunoglobulin-like domains, and a heparin-binding domain
(Plotnikov et al., 2000; Itoh and Ornitz, 2004). Immunoglobulin domains have a characteristic fold built up of a sandwich of two β sheets containing antiparallel strands linked by a disulphide bond. These domains have no enzymatic activity, but are important for determining ligand specificity (Dell and Williams, 1992; Barclay, 2003). Alternative mRNA splicing of the FGFR genes regulates the number (two or three) of immunoglobulin domains and dictates the sequence of the immunoglobulin domain III, resulting in isoforms IIIb and
IIIc, which are important for determining ligand-binding specificity (Givol and Yayon, 1992;
Ornitz and Itoh, 2001; Itoh and Ornitz, 2004). This splicing naturally occurs in the FGFR1,
FGFR2, and FGFR3 genes, but not in the FGFR4 gene (as reviewed by Li et al., 2016).
The HS cofactors are components of proteoglycans on the cell surface and in the pericellular matrix that bind both FGF and FGFR to facilitate and stabilize their interaction
(Yayon et al., 1991; Mohammadi et al., 2005; Li et al., 2016). For endocrine FGFs (including
FGF19, FGF21, and FGF23), that have little affinity for HS, the transmembrane proteins
Klotho/betaKlotho are important to facilitate binding to FGFRs (Goetz et al., 2007). Variation in sulfated domains of HS and in affinity to cofactors contribute to differences in FGF signaling activities in addition to FGFRs diversity (Guimond and Turnbull, 1999; Merry et al., 1999; Ye et al., 2001).
The binding of ligands to FGFRs causes receptor dimerization, transphosphorylation, and activation of the intracellular tyrosine kinase domain (Kelleher et al., 2013). Intracellular 6
tyrosine kinase takes part in signal transduction to the nucleus, stimulating mitogenesis
(Radha et al., 1996; Ruetten and Thiemermann, 1997). Tyrosine autophosphorylation of receptors by tyrosine kinase is essential for the recruitment and activation by phosphorylation of many downstream cytoplasmic targets and subsequent initiation of dynamic signaling cascades (Dengjel et al., 2009; Goetz and Mohammadi, 2013). The main signaling pathways downstream of receptors for tyrosine kinase are: Ras/MAPK (mitogen-activated protein kinase) signaling cascades, which regulate cell proliferation; signaling pathways involving phospholipid second messengers via PLCγ (phospholipase C-γ) for regulation of cell motility;
PI3K (phosphatidylinositol 3-kinase) for regulation of cell survival; and the STATs (signal transducers and activator of transcription) pathway (Dengjel et al., 2009; Goetz and
Mohammadi, 2013). Nevertheless, for activation of the Ras/MAPK and the PI3K pathways to occur, the docking protein FRS2α needs to be phosphorylated in its tyrosine and serine/threonine residues, which occurs upon binding of FGF to its receptor (Kouhara et al.,
1997; Gotoh, 2008; Ornitz and Itoh, 2015). The specificity of signal transduction at this initial stage is determined in great extent by the amino acid sequence surrounding the phosphorylated tyrosine residue (Dengjel et al., 2009).
2. Role of fibroblast growth factors on ovarian physiology
FGFs were first reported in the ovary in 1977 (Gospodarowicz et al., 1977b;
Gospodarowicz et al., 1977c), when FGF1 was found to stimulate proliferation of bovine granulosa cells (GC) and theca cells (TC). From these pioneer studies to present, ten members of the FGF family have been described in the ovary of mammals, including FGF1 (Berisha et al., 2004), FGF2 (Berisha et al., 2000), FGF7 (Parrott and Skinner, 1998), FGF8 (Buratini et al., 2005a), FGF9 (Drummond et al., 2007; Schreiber and Spicer, 2012), FGF10 (Castilho et al., 2015), FGF16 (Ferreira et al., 2016), FGF17 (Machado et al., 2009), FGF18 (Portela et al., 2010), and FGF22 (Castilho et al., 2015), each with autocrine, paracrine, and endocrine
7
roles in the regulation of development of ovarian follicles (for reviews, see Chaves et al.,
2012; Price, 2016).
Ovarian folliculogenesis is a highly regulated process by which the female oocyte develops within the somatic cells of the ovary, GC and TC, and matures into a fertilizable ovum (Eppig, 1991; Richards, 1994; Elvin and Matzuk, 1998; McGee and Hsueh, 2000;
Ackert et al., 2001). Ovarian follicles develop through primordial, primary, and secondary stages before an antral cavity is formed (McGee and Hsueh, 2000). These preantral follicles remain in a dormant stage until primordial follicle activation occurs, followed by growth of both the oocyte and follicle somatic cells (Fortune et al., 2000). This process happens in the fetal life of domestic animals and primates and in early neonatal period of rodents and rabbits
(Hirshfield, 1991; Van den Hurk et al., 1997; Fortune et al., 2000; Fortune, 2003).
The factors that stimulate development of preantral follicles are dependent on species and stage of follicles and include insulin, growth differentiation factor-9 (GDF-9), estradiol, insulin-like growth factor-1 (IGF-1), epidermal growth factor (EGF), follicle stimulating hormone (FSH), and luteinizing hormone (LH), among others (McGee and Hsueh, 2000;
Fortune, 2003; Hsueh et al., 2015). Nevertheless, the gonadotropins (FSH and LH) are unlikely to exert direct actions on primordial follicles because these structures lack gonadotropins receptors, so they start to be important beginning at the stage of primary follicles in some species, such as porcine and murine, and in small secondary follicles in other species, such as bovine (Hsueh et al., 1984; McGee and Hsueh, 2000; Fortune et al., 2003).
Among the factors aforementioned, FGFs also have been reported to act in development of early stages of follicular development.
The production of FGFs within the ovary starts early in folliculogenesis: FGF2 was found in oocytes of immature bovine follicles (van Wezel et al., 1995); FGF7 has been reported in primordial, primary, and secondary follicles of cattle (Berisha et al., 2004;
Buratini et al., 2007); FGF9 protein was found in the ovary of immature rats, located in
8
stromal cells and basement membranes surrounding GC as well as in TC precursors
(Drummond et al., 2007); FGF10 mRNA was detected in primordial, primary, and secondary follicles of cattle (Buratini et al., 2007). In addition, at least two members of the FGF family are reported to have an active role in preantral follicle development: FGF2 and FGF7. FGF2 was found to stimulate GC proliferation of preantral follicles in cattle (Wandji et al., 1996), transition of primordial follicles into primary follicles in rats (Nilsson, et al., 2001) and preantral follicle growth and survival in women (Wang et al., 2014) while FGF7 was found to stimulate preantral follicle development in rats (Hsueh et al., 2000; Kezele et al., 2005).
These observations imply a role of FGFs in early folliculogenesis.
Members of the FGF family were also detected in antral follicles and in corpora lutea
(Parrott and Skinner, 1998; Berisha et al., 2000; Castilho et al., 2008; Cho et al., 2008). After acquiring an antral cavity, a small group of follicles is recruited to initiate follicular growth towards ovulation (Bao and Garverick, 1998). Nevertheless, most of them undergo atretic degeneration while only a few of them will be selected to become the dominant follicles, which are larger than the subordinate follicles and will ovulate to release the mature oocyte for fertilization (Spicer and Echternkamp, 1986; McGee and Hsueh, 2000). The recruitment of a cohort of growing antral follicles and subsequent selection of dominant follicles is not only regulated by gonadotropic hormones, but also by factors produced by the oocyte and surrounding follicular cells (Eppig, 2001; Fortune et al., 2004). Hence, the presence of FGFs in antral follicles indicates their importance in all stages of folliculogenesis.
In antral follicles of cattle, FGF1, FGF2, FGF7, FGF18, and FGF22 are mainly produced by TC (Parrott and Skinner, 1998; Berisha et al., 2000; Berisha et al., 2004; Buratini et al., 2007; Portela et al., 2010; Castilho et al., 2015); FGF8 is produced by GC, TC, and oocytes (Buratini et al., 2005); FGF9 is produced in greater amounts in GC than in TC
(Schreiber et al., 2012); FGF10 is produced by TC and oocytes (Buratini et al., 2007); FGF16 is produced by the oocyte (Ferreira et al., 2016); and FGF17 is detected mainly in oocytes, but also in GC (Machado et al., 2009). Interestingly, the production of some FGFs also 9
change according to the diameter of bovine antral follicles: FGF2 and FGF7 mRNA abundance, for example, is greater in large than in small follicles (Parrott and Skinner, 1998;
Berisha et al., 2000; Berisha et al., 2004) while FGF9 mRNA abundance is greater in small than in large follicles (Schreiber et al., 2012). Nevertheless, some FGFs such as FGF1
(Berisha et a., 2004; Berisha et al., 2006) and FGF22 (Castilho et al., 2015) do not change during antral follicular growth in cattle.
2.1 Role of fibroblast growth factors and gonadotropins on ovarian steroidogenesis
In response to gonadotropins (FSH and LH) secreted by the pituitary, the different compartments of the ovarian follicle interact in a highly integrated way to synthesize and secrete sex steroids (estrogens, progestins) in order to produce a fertilizable egg (Hsueh et al.,
1984). Estradiol, the main estrogen produced in ovarian follicles, has direct effects on GC, stimulating cell proliferation, enhancing LH receptor formation and FSH-stimulated aromatase activity (Hsueh et al., 1984; Kessel et al., 1985), being therefore essential for development and survival of dominant follicles (Spicer and Echternkamp, 1986; Evans and
Fortune, 1997; Robker and Richards, 1998). Besides providing an uterine environment to maintain pregnancy (Keyes and Wiltbank, 1988; Lonergan et al., 2007), progesterone also plays a role in the control of preovulatory follicle maturation: it increases close to the time of ovulation (Fortune and Hansel, 1995), regulates the time of release of prostaglandin F2α for luteolysis (Silvia et al., 1991; dos Santos et al., 2009), and regulates the release of LH and
FSH by the pituitary, in addition to modulating pituitary responsiveness to gonadotropin- releasing hormone (GnRH) from the hypothalamus (Chang and Jaffe, 1978; Mahesh and
Muldoon, 1987).
Follicular steroid production is crucial for maintenance and development of growing follicles and are dependent upon stimulation of FSH and LH, which regulate several key enzymes, such as cytochrome P450 side-chain cleavage enzyme (P450scc), cytochrome P450
17α- hydroxylase (17αOH), 3β-hydroxysteroid dehydrogenase (3β-HSD), and cytochrome
P450 aromatase as well as the cholesterol transport protein, steroidogenic acute regulatory 10
protein (StAR) (Richards, 1994; Tian et al., 1995; Bao and Garverick, 1998; McGee and
Hsueh, 2000; Logan et al., 2002; Orisaka et al., 2006). Each of these enzymes catalyzes a key step in the biosynthesis of steroids and their expression changes according to the type of cell and stage of follicle development (Tian et al., 1995; Bao and Garverick, 1998; Logan et al.,
2002). As reviewed by Richards (1994), P450scc converts cholesterol into pregnenolone, 3β-
HSD converts pregnenolone into progesterone, 17αOH converts progesterone to androstenedione, and aromatase converts androgens into estrogens.
LH plays a key role in determining the differentiation of TC in preovulatory follicles since, in these follicles, TC have high amounts of LH receptor and 17αOH and therefore synthesize great quantities of androgens (Richards, 1994; Tian et al., 1995; McGee and
Hsueh, 2000). Androgens produced by TC are converted into estrogens by aromatase present in GC, and high concentrations of estrogens, in synergism with FSH, stimulate GC differentiation of large preovulatory follicles (Hsueh et al., 1984; Richards, 1994; McGee and
Hsueh, 2000; Fortune et al., 2004). Moreover, in preovulatory follicles, FSH stimulates mRNA expression for P450scc, LH receptor, and StAR in GC, resulting in an increase in progesterone production by these cells (Orisaka et al., 2006).
FGFs diverge in their effects over steroidogenesis and subsequently over follicular survival. To date, from the ten members of the FGF family detected in the ovary, at least eight have effects on ovarian steroidogenesis: FGF1, FGF2, FGF7, FGF8, FGF9, FGF10, FGF17, and FGF18.
In cattle, FGF1 had no effect on progesterone production by GC (Schams et al.,
2001). In contrast, FGF1 stimulates progesterone production by ovine luteal cells collected from day 5 of the estrous cycle, with no effects on luteal cells collected on later stages (days
10 and 15) of the estrous cycle (Grazul-Bilska et al., 1995). In pigs, FGF1 inhibited progesterone secretion by GC (Biswas et al., 1988), suggesting that differences exist among species in the ovarian cells in response to FGF1.
11
FGF2 effects on steroidogenesis have been extensively studied, indicating that FGF2 inhibits FSH-stimulated estradiol production and aromatase activity by rat (Baird and Hsueh,
1986; Yamoto et al., 1993) and bovine GC (Vernon and Spicer, 1994; Wandji et al., 1996).
Also, FGF2 inhibits LH-stimulated progesterone and androstenedione production by bovine
GC (Spicer and Stewart, 1996; Wandji et al., 1996). In contrast, FGF2 enhanced FSH-induced progesterone production by rat GC when FSH was used at suboptimal concentrations (Baird and Hsueh, 1986), and stimulated LH-induced production of both estradiol and progesterone by rat GC (Yamoto et al., 1993). These latter results imply that effects of FGF2 on steroidogenesis may change not only according to species, but also according to other factors such as the dose and type of gonadotropin used and developmental status of follicles when
GC were collected.
FGF7 inhibits FSH-stimulated estradiol production and aromatase activity by bovine and rat GC and suppresses hCG-stimulated progesterone production by bovine GC (Parrott and Skinner, 1998) and human GC (Osuga et al., 2001).
FGF8 suppresses FSH-induced estradiol production by rat GC with no effects on production of progesterone and cAMP induced by FSH and forskolin (Miyoshi et al., 2010;
Miyoshi et al., 2012).
FGF9 has divergent roles on steroidogenesis, depending on the species. In rats, progesterone production by GC was increased by FGF9 when stimulated by FSH, but not by
LH (Drummond et al., 2007), implying that the FGF9 stimulatory effect on progesterone production may be dependent on degree of differentiation of GC. Drummond and colleagues
(2007) also observed a stimulatory effect of FGF9 in mRNA levels for the steroidogenic enzymes StAR and P450scc in rat GC, with an inhibitory effect of a high dose of FGF9 on
3β-HSD mRNA in the presence of FSH. In pigs, FGF9 increased estradiol production by GC with inconsistent effects on progesterone production by GC, stimulating progesterone production in the presence of FSH, but inhibiting progesterone production in the presence of
12
FSH and IGF1 (Evans et al., 2014). In cattle, in contrast to what was observed for rats and pigs, FGF9 attenuated GC production of progesterone and estradiol stimulated by IGF-1
(Schreiber and Spicer, 2012). Schreiber and Spicer (2012) also showed that FGF9 decreased mRNA abundance for FSH receptor and the steroidogenic enzyme P450scc in GC of both small and large follicles with no effects on aromatase or StAR mRNA abundance. In bovine
TC, FGF9 also had inhibitory effects on steroidogenesis, attenuating IGF-1 stimulated production of both androstenedione and progesterone and decreasing mRNA abundance for
LH receptor and for P450scc enzyme and 17-α-hydroxylase in cells cultured with LH and
IGF-1, with no effect on abundance of StAR mRNA (Schreiber et al., 2012).
FGF10 not only suppresses FSH-stimulated estradiol production by bovine GC
(Buratini et al., 2007), but also decreased mRNA abundance for FSH receptor and for aromatase, with no effects on mRNA levels for STAR or the steroidogenic enzymes 3β-HSD and P450scc (Castilho et al., 2015).
FGF17 treatment decreased FSH-stimulated estradiol and progesterone secretion by bovine GC from small follicles in diameter (Machado et al., 2009).
FGF18 is a powerful suppressor of ovarian steroidogenesis in cattle (Portela et al.,
2010), inhibiting FSH-stimulated estradiol and progesterone by GC in a dose-dependent manner as well as decreasing mRNA abundance for STAR and FSH receptor as well as decreasing aromatase, P450scc, 3β-HSD, and hydroxysteroid (17-β) dehydrogenase 1 mRNA abundance.
2.2 Role of fibroblast growth factors in proliferation of granulosa and theca cells
Members of the FGF family have been reported in many studies as powerful mitogens, acting in many organs and cell types to stimulate cell proliferation (for reviews, see
Finch et al., 1989; Rodan et al., 1989; Igarashi et al., 1998; Skaletz-Rorowski et al., 1999;
Boilly et al., 2000). These growth factors bind to tyrosine-kinase receptors to activate
13
Ras/MAPK signaling cascades to stimulate cell proliferation (Dailey et al., 2005; Dengjel et al., 2009), as well as organ development (Hogan, 1999; Metzger and Krasnow, 1999), wound healing (Wahl et al., 1989; Li et al., 2016), tumor formation (Ornitz and Itoh, 2001; Tanner and Grose, 2015), and more recently, ovarian folliculogenesis (Chaves et al., 2012; Price,
2016).
In ovarian follicular development, the compartments of the follicles, namely oocyte,
GC, and TC, communicate in paracrine ways to stimulate somatic cell proliferation and follicular development. Presently, at least four members of the FGF family are known to stimulate bovine ovarian follicle cell proliferation: FGF1, FGF2, FGF7, and FGF9
(Gospodarowicz et al., 1977b; Gospodarowicz et al., 1977c; Gospodarowicz et al., 1985;
Parrott et al., 1994; Spicer and Stewart, 1996; Schreiber and Spicer, 2012). In chickens, FGF1 and FGF2 stimulate both GC and TC proliferation whereas FGF5 and FGF7 have no effect
(Roberts and Ellis, 1999), suggesting that species differences may exist in terms of which
FGF is mitogenic in the follicle.
It has been proposed that oocytes carry out this intrafollicular conversation by secreting factors that affect GC morphology, which in turn affect the oocyte (Eppig, 2001;
Matzuk et al., 2002) and theca interna (Liu et al., 2015). Indeed, among other factors, bone morphogenesis protein-15 (BMP-15) and GDF-9 are derived from mammalian oocytes to stimulate GC proliferation (Otsuka et al., 2000; Vitt et al. 2000; Spicer et al., 2006), TC proliferation, and theca interna development (Spicer et al., 2008; Liu et al., 2015). Within the
FGF family, at least four members are currently known to be secreted by the oocyte of mammalian antral follicles, including FGF8, FGF10, FGF16, and FGF17 (Buratini et al.,
2005a; Buratini et al., 2007; Sugiura et al., 2007; Machado et al., 2009; Santos-Biase et al.,
2012; Ferreira et al., 2016), and only FGF8 appears to be stimulating GC proliferation, since it leads to expression of genes related to cell proliferation, such as MAPK3/1 and MAPK14, in GC (Jiang et al., 2013; Price, 2016). Future research is needed to verify if FGF8 is indeed
14
stimulating GC proliferation and if other FGFs are produced by the oocyte to stimulate proliferation of surrounding somatic cells.
Among FGFs that stimulate somatic cell proliferation of bovine ovarian antral follicles, FGF1, FGF2, and FGF7 are mainly produced by TC (Parrott and Skinner, 1998;
Berisha et al., 2000; Berisha et al., 2004; Buratini et al., 2007), while the major producers of
FGF9 are GC (Schreiber et al., 2012). FGF1, FGF2, and FGF9 stimulate both GC and TC proliferation in either autocrine or paracrine ways (Gospodarowicz et al., 1977b;
Gospodarowicz et al., 1977c; Gospodarowicz et al., 1985; Spicer and Stewart, 1996;
Schreiber and Spicer, 2012; Schreiber et al., 2012) whereas FGF7 stimulates GC proliferation in a paracrine way (Parrott et al., 1994).
2.3 Role of fibroblast growth factors in ovarian follicular fate
Besides stage of folliculogenesis and species, another important factor associated with the production of FGFs in antral follicles is follicular health (Buratini et al., 2007;
Portela et al., 2010). It is now well accepted that antral follicles grow and develop until they reach one of two fates: ovulation or atresia, the latter occurring in the vast majority of the follicles (Hirshfield, 1988; Chun et al., 1994; Jolly et al., 1994; McGee and Hsueh, 2000).
Follicular atresia is characterized as a degenerative process associated with apoptosis, occurring mainly in GC of many species, including rats (Hughes and Gorospe, 1991; Chun et al., 1995) and cattle (Rajakowski, 1960; Jolly et al., 1994; Evans et al., 2004). Ovarian follicles in all stages of growth and at any stage of life until the occurrence of reproductive senescence are susceptible to undergo atresia (Hughes and Gorospe, 1991). In cattle, an increase in the rate of atresia of large antral follicles is observed as the estrous cycle advances toward ovulation (Spicer and Echternkamp, 1986). In rats, a dramatic increase in numbers of atretic follicles appears just after ovulation (Hirshfield, 1988). Among other features, atretic follicles are characterized by pyknosis of the nuclei and fragmentation of DNA in GC, a decreased aromatase activity, and thus, estrogen production (Hughes and Gorospe, 1991;
Jolly et al., 1994; Chun et al., 1994; van Wezel et al., 1999). Atretic follicles are also 15
characterized by TC with LH receptors uncoupled from adenylate cyclase, which are incapable of synthesizing steroids in response to LH, resulting in a reduction in theca androgen synthesis concomitant with an increased output of progesterone (McNatty et al.,
1985) and TC hypertrophy (Rajakowski, 1960; Bukovsky et al., 1993). Therefore, large antral follicles that are selected to escape atresia to become dominant and ovulate have a high estrogen to progesterone ratio (Ireland and Roche, 1982; Spicer and Echternkamp, 1986). To date, members of the FGF family that appear to be associated with health of large antral follicles include FGF1 (Schams et al., 2009), FGF2 (Tilly et al., 1992; Lynch et al., 2000),
FGF7 (Castilho et al., 2015), FGF8 (Sugiura et al., 2007; Miyoshi et al., 2010), FGF9
(Schreiber and Spicer, 2012), FGF10 (Buratini et al., 2007), FGF17 (Machado et al., 2009), and FGF18 (Portela et al., 2010). Depending on the species, these FGFs can stimulate survival or atresia of large follicles and their production change according to health of the follicles.
In cattle, FGF1 and FGF8 appear to be contributing to follicular survival. FGF1 stimulates bovine GC and TC proliferation (Gospodarowicz et al., 1977b; Gospodarowicz et al., 1977c) while polymorphisms of the FGF8 gene were associated with the number of oocytes collected by ovum pick up (Santos-Biase et al., 2012), suggesting possible roles for this growth factor in follicular development.
As already mentioned in this review, FGF2, FGF7, FGF9, FGF10, FGF17, and
FGF18 inhibit steroidogenic enzymes activity and FSH-stimulated estradiol production by
GC in cattle (Vernon and Spicer, 1994; Parrott and Skinner, 1998; Buratini et al., 2007;
Machado et al., 2009; Portela et al., 2010; Schreiber and Spicer, 2012; Castilho et al., 2015).
Because estradiol production is important for GC survival and differentiation of dominant follicles (Knecht et al., 1985; Fortune et al., 2004), FGFs suppressing estradiol production may be inducing atresia or preventing differentiation of GC in cattle. In agreement with this idea is the fact that mRNA abundance for FGF9, FGF10, FGF17, and FGF18 in bovine GC or TC is greater in subordinate or atretic follicles than in dominant follicles (Buratini et al., 16
2007; Machado et al., 2009; Portela et al., 2010; Schreiber et al., 2012; Castilho et al., 2015).
As mentioned above, FGF2, FGF7, and FGF9 stimulate bovine GC proliferation (Parrott et al., 1994; Spicer and Stewart, 1996; Schreiber and Spicer, 2012), and thus may act as anti- differentiation factors rather than stimulating follicular atresia in cattle. Although FGF10 does not stimulate GC proliferation (Buratini et al., 2007), FGF10 stimulates cumulus expansion and glucose uptake by the cumulus-oocyte complex in cattle (Caixeta et al., 2013), indicating that it may play a role in oocyte growth, maturation, and ovulation (Zuelke and Bracket,
1992; Chen et al., 1993; Downs et al., 1996; Sutton-McDowall et al., 2004). On the other hand, FGF18 induced regression of the dominant follicle when injected in vivo and increased cleaved caspase-3 in GC in vitro (Portela et al., 2015), which is a major downstream effector of apoptosis and serves a marker for GC apoptosis (Feranil et al., 2005), confirming the role for this protein in induction of atresia in bovine antral follicles.
In addition to their roles in folliculogenesis of cattle, FGFs have been shown to play roles in development of antral follicles of other species. FGF1 and FGF2 mRNA abundance is greater in TC of porcine periovulatory follicles (Schams et al., 2009), suggesting a positive role of these FGFs in follicular survival in this species. FGF2 seems to stimulate antral follicle survival of rats, since it stimulates the production of both estradiol and progesterone of rat GC (Yamoto et al., 1993) while inhibiting apoptosis of rat GC (Tilly et al., 1992). FGF8 appears to be important in antral follicle development in mice, since it acts to stimulate glycolysis of mouse cumulus cells, which is important to provide energy to the oocyte
(Sugiura et al., 2007), but, in rat GC, FGF8 suppressed FSH-induced estradiol production
(Miyoshi et al., 2010), what could imply a role in atresia in this species. Similarly, FGF9, as previously mentioned in this review, has stimulatory effects on steroidogenesis of murine
(Drummond et al., 2007) and porcine GC (Evans et al., 2014), implying a role in antral follicle survival in these species.
2.4 Role of fibroblast growth factors in luteal function
17
Some FGFs appear also to influence formation and function of the corpus luteum.
The corpus luteum is a transient endocrine gland in the adult ovary that forms from the ruptured follicle after ovulation and secretes progesterone to allow implantation of the early embryo in the endometrium and to provide a uterine environment that sustains pregnancy (as reviewed by Keyes and Wiltbank, 1988). From the 22 known members of the FGF family, at least FGF2, FGF7, FGF9, and/or FGF10 have been detected in corpus luteum of rats
(Guthridge et al., 1992; Drummond et al., 2007) and cattle (van Wezel et al., 1995; Salli et al.,
1998; Castilho et al., 2008).
In cattle and sheep, FGF1 seems to be contributing to early development of corpus luteum, stimulating luteal cell proliferation (Gospodarowicz et al., 1977b; Grazul-Bilska et al., 1995) and progesterone production of ovine luteal cells early (i.e., day 5) in the estrous cycle (Grazul-Bilska et al., 1995). Nevertheless, FGF1 may also be involved in luteolysis in cattle (Neuvians et al., 2004).
Similarly, FGF2 stimulates progesterone production by luteal cells from cattle
(Miyamoto et al., 1992), sheep (Grazul-Bilska et al., 1995), and rats (Tamura et al., 1991).
FGF2 has also been reported to stimulate angiogenesis (Cross and Claesson-Welsh, 2001;
Robinson et al., 2008), a prominent characteristic of the corpus luteum formation (Keyes and
Wiltbank, 1988), being present in vascular cells of early bovine corpus luteum (Schams et al.,
1994) and in cytoplasm of endothelial cells of the capilary bed of theca interna and in larger vessels of the theca externa of mature bovine follicles (Berisha et al., 2000). In particular, vascular endothelial growth factor A (VEGFA) and FGF2 synergized to increase bovine luteal endothelial cell networks (Robinson et al., 2008), and intracellular injections of antibodies against either VEGFA or FGF2 markedly reduced corpus luteum volume and plasma progesterone concentrations (Yamashita et al., 2008). Therefore, formation and regulation of corpus luteum is another feature of FGFs in reproduction of mammals.
2.5 Role of fibroblast growth factor receptors on ovarian physiology
18
The FGFR is a single chain transmembrane tyrosine kinase with two or three immunoglobulin-like domains and a heparin-binding sequence in the extracellular ligand- binding portion (Ornitz and Itoh, 2001; Itoh and Ornitz, 2004; Li et al., 2016). As previously mentioned in this review, there are four distinct genes encoding for FGFRs (FGF1-FGF4) in vertebrates and mRNA alternative splicing occurs in the immunoglobulin-like domains III of the FGFR1, FGFR2, and FGFR3 genes (but not of FGFR4), generating diversity of sequence and resulting in various isoforms (Itoh and Ornitz, 2004; Ornitz and Itoh, 2015; Li et al.,
2016). The ligands of the FGF family have different affinities for these receptors (Itoh and
Ornitz, 2004), which are determined by the immunoglobulin-like domains (Dell and
Williams, 1992).
Because FGFRs have different ligand-binding specificities (see Table 2), the localization of FGFRs in the different follicle compartments is of fundamental importance for the FGFs to exert their effects on ovarian physiology. Of the ligands in this growth factor family that are produced in the ovary, the main receptors, according to ligand binding specificity, that would be expected to be present in order for cells to respond to them are:
FGFR1c and FGFR3c for FGF1 and FGF2; FGFR2b followed by FGFR1b for FGF7, FGF10, and FGF22; FGFR3c followed by FGFR4 for FGF8, FGF17, and FGF18; and FGFR3c followed by FGFR2c for FGF9 and FGF16 (Ornitz and Itoh, 2015). Evidence clearly shows species differences exist in terms of which of these FGFRs exist in ovarian cells.
In cattle, FGFR1c mRNA, the preferred receptor for FGF1 and FGF2, has been detected in oocytes and in cumulus cells, increasing in response to FSH treatment (Zhang and
Ealy, 2012). In chickens, FGFR1 mRNA and protein are intensely expressed in GC and are critical for FGF1-induced GC proliferation (Lin et al., 2012). Therefore, FGFR1c in cattle and
FGFR1 in chickens seem important for the actions of FGF1 in promoting follicular development. In rats, FGFR1 mRNA was detected in ovaries during proestrus, estrus, and metestrus, but not during diestrus (Asakai et al., 1994). Interestingly, no FGFR1 immunostaining was detectable in human oocytes or GC (Ben-Haroush et al., 2005). 19
FGFR2b, the main receptor for FGF7, FGF10, and FGF22, is detected in GC and oocytes of cattle (Berisha et al., 2004; Buratini et al., 2007; Machado et al., 2009; Zhang and
Ealy, 2012), while FGFR1b, the second most important receptor for these growth factors, is detected in bovine GC, TC, and oocytes (Zhang and Ealy, 2012; Castilho et al., 2015). As previously mentioned in this review, FGF7 and FGF10, produced by TC, decrease aromatase activity of GC (Parrot and Skinner, 1998; Castilho et al., 2015) and thus appear to play a role in anti-differentiation of these cells. Interestingly, FGFR2b and FGFR1b GC mRNA are both greater in future subordinate follicles than in future dominant follicles (Castilho et al., 2015), and this reinforces the idea that FGFs from this subfamily impede GC to differentiate and therefore may regulate follicle selection in cattle. In pigs, a polytocous species, different than in cattle, FGFR2b mRNA abundance is greater in TC than in GC, and greater in theca interna of large and preovulatory follicles than in those of small and medium follicles (Schams et al.,
2009), suggesting a role for FGF7 and FGF10 in differentiation of TC in this species.
FGFR2c, the second main receptor for FGF9 and FGF16, has been detected in both bovine GC and TC, without changes in final follicular growth in cattle (Berisha et al., 2004).
Little is currently known about the FGF16 functions in GC and TC, but FGF9, as stated earlier in this review, has effects on proliferation and steroidogenesis of both GC and TC in different sizes of antral follicles (Schreiber and Spicer, 2012; Schreiber et al., 2012) and may therefore rely on this receptor in all moments of folliculogenesis in cattle. In pigs, Schams and colleagues (2009) reported a greater FGFR2c mRNA in TC from large follicles with no differences for mRNA abundance of this isoform in GC among different sizes of follicles. In contrast, in a more recent study, Evans and coauthors (2014) reported a greater GC FGFR2c mRNA abundance in large than in small and medium follicles of gilts. Still, taken together, these observations imply a role for FGF9 in final maturation of ovarian follicles in pigs, and are in agreement with the observation that FGF9 stimulates estradiol production by GC in this species (Evans et al., 2014), as already mentioned in this review.
20
Bovine FGFR3c, the main receptor for FGF8, FGF9, FGF16, FGF17, and FGF18 was detected in both GC and TC, but not in the oocyte, and increased in GC (but not in TC) of small healthy follicles and in response to FSH (Buratini et al. 2005a), implying a role for these FGFs in early stages of antral follicle development in cattle. In rats, FGFR3 protein levels were detected in oocytes, GC, TC, and corpora lutea (Drummond et al., 2007), suggesting an important role for ligands such as FGF9, an inducer of rat GC progesterone production (Drummond et al., 2007) in folliculogenesis of this species.
Bovine FGFR4, the second most important receptor for FGF8, FGF17, and FGF18, has been detected in TC, but not in GC or oocytes of antral follicles, being greater in small than in large follicles (Buratini et al., 2005a). Since FGF17 and FGF18 are apparently involved in follicular atresia, it is likely that they would be exerting this role in a receptor that is predominant in small antral follicles, since large follicles are being selected for dominance and ovulation. In mice, FGFR4 mRNA has been detected in GC, but not in TC or oocytes, during most phases of folliculogenesis (Puscheck et al., 1997). In human follicles, FGFR4 immunostaining was most prevalent in oocytes but also existed in GC and stromal cells (Ben-
Haroush et al., 2005).
As already mentioned in this review, the intraovarian production of FGFs start early in folliculogenesis. So, for these FGFs to have an effect, FGFRs must also need to be present.
Indeed, mRNA encoding at least four FGFRs has currently been detected in fetal bovine preantral follicles, including FGFR1b, FGFR2b, FGFR3c, and FGFR4 (Buratini et al., 2005b;
Castilho et al., 2014). In addition, in mice, FGFR4 mRNA has been detected in GC of primary, secondary, and preantral follicles (Puscheck et al., 1997). Such observations confirm the importance of the FGF family in all stages of folliculogenesis in mammals.
3. Role of other growth factors on ovarian physiology
In addition to FGFs, aforementioned in this review, other growth factors are critical for folliculogenesis. Among these factors, members of the IGF system and the transforming
21
growth factor β family deserve special attention for their contribution in development of ovarian follicles.
3.1 IGF system
The growth factors IGF-1 and IGF-2 are single-chain polypeptides functionally and structurally related to insulin, first isolated from human plasma in the 1970s (Rinderknecht and Humbel, 1976; Rinderknecht and Humbel, 1978a; Rinderknecht and Humbel, 1978a;
Zapf et al., 1984). The IGFs are mainly produced by the liver to be released in the circulation in order to stimulate endocrine actions in target cells, but are also locally produced in tissues to have a paracrine or autocrine actions (for review, see Sara and Hall, 1990). These actions include DNA and protein synthesis (Canalis, 1980; Zapf et al., 1984), cell proliferation
(Frödin and Gammeltoft, 1994), decreased lipolysis (Zapf et al., 1978), increased glucose transport and oxidation (Schwartz and Goodman, 1976; Guler et al., 1987), and increased glycogenesis (Froesch et al., 1985; Parkes et al., 1986; Zapf et al., 1986) on various tissues.
Because of their potent mitogenic effects, IGFs have also been reported in cancer of various tissues (Myal et al., 1984; Mattsson et al., 1986; Pollak et al., 1990; Halje et al., 2012).
For IGFs to exert their actions, they bind to two receptors, type 1 and type 2 IGF receptors (IGF-1 receptor and IGF-2 receptor, respectively), in various target tissues (Sara and Hall, 1990). The IGF-1 receptor is a glycoprotein consisting of two extracellular α- subunits linked via disulfide bonds with two transmembranal β-subunits with tyrosine-kinase activity, sharing a structural and functional similarity with the insulin receptor (Massagué and
Czech, 1982; Morgan et al., 1986; LeRoith et al., 1995). The binding of the ligand to the extracellular subunits results in intracellular signal transduction by autophosphorylation of tyrosine residues within the intracellular subunits (Morgan et al., 1986). Distinct from the
IGF-1 receptor, the IGF-2 receptor is monomeric and does not have intrinsic tyrosine kinase activity, but is phosphorylated on tyrosine residues (Laureys et al., 1988; Schmid, 1995). The
IGF-1 receptor has a higher affinity for IGF-1 than for IGF-2, and a low affinity for insulin, while the IGF-2 receptor has a higher affinity for IGF-2 than for IGF-1, with no affinity for 22
insulin (Massagué and Czech, 1982; Schmid, 1995; Sara and Hall, 1990). Current evidence suggests that IGF-2 receptor is acting as a decoy receptor, inactivating IGF-2 in a similar way to IGFBPs (Spicer and Aad, 2007; Aad et al., 2013).
Effects of IGFs in the ovary of various species have been reported more than three decades ago (Savion et al., 1981; Baranao and Hammond, 1984). Since then, these polypeptides have been described to be important regulators of ovarian follicular cells proliferation, steroidogenesis, and selection of dominant follicles in various species (Adashi et al., 1991; Spicer and Echternkamp, 1995). In addition, synthesis of IGFs by ovarian follicular cells to stimulate autocrine and paracrine actions is under regulation of various hormones (Spicer and Echternkamp, 1995).
The roles of IGFs start early in folliculogenesis with mRNA expression for IGFs and
IGF receptors being detected in different stages of preantral follicle development (Silva et al.,
2009). In goats, IGF-1 and IGF-2 stimulated early antrum formation and oocyte growth, survival, and competence of prentral follicles (Zhou and Zhang, 2005; Magalhães-Padilha et al., 2012; Duarte et al., 2013). In mice, IGF-1 stimulated oocyte competence of preantral follicles in vitro (Jee et al., 2012). In buffalo, expression of IGF-2 and IGF receptors was detected in oocyte, GC, and TC of preantral follicles (Dubey et al., 2015). In primates, in vitro androgen increased IGF receptors in the oocytes of primordial follicles and increased the number of primary follicles, suggesting that the IGF system may be important for primordial follicle entry into the growth pool (Vendola et al., 1999). In humans, IGF-1 and IGF-1 receptor mRNA and protein have been detected in preantral follicles and IGF-1 stimulated initiation of preantral follicle growth (Stubbs et al., 2013). In cattle, IGF-1 receptor mRNA was detected in oocytes, GC and TC of preantral follicles, suggesting a role for the IGF system in early folliculogenesis (Amstrong et al., 2000; Amstrong et al., 2002).
In bovine antral follicles, IGF-1 mRNA has been mainly detected in GC and IGF-2 mRNA has been mainly detected in TC (Spicer et al., 1993; Yuan et al., 1998; Schams et al.,
23
2002) while IGF-1 receptor mRNA has been detected in GC, TC, and oocytes (Schams et al.,
2002; Armstrong et al., 2002) and IGF-2 receptor mRNA has been detected in GC and TC
(Spicer and Aad, 2007; Aad et al., 2013). Because IGF-2 has a greater expression than IGF-1 in the bovine ovary (Armstrong et al., 2000), it is currently believed that IGF-2 is the main intrafollicular IGF ligand, performing paracrine and autocrine actions while most of IGF-1 comes from the liver to elicit endocrine effects in this species (Velazquez et al., 2008). In rats,
IGF-1 mRNA is expressed in GC, but not in TC whereas IGF-2 mRNA is present in TC but not GC (Oliver et al., 1989; Hernandez, 1995). In human small antral follicles, IGF-1 and
IGF-2 mRNA detection was restricted to TC while IGF-1 receptor mRNA was detected exclusively in GC and IGF-2 receptor was detected in both GC and TC; in dominant follicles, no IGF-1 mRNA has been detected, IGF-2 mRNA has been detected exclusively in GC, IGF-
1 receptor mRNA has been detected in GC, and IGF-2 receptor has been detected in both TC and GC (el-Roeiy et al., 1993). In porcine antral follicles, IGF-1 mRNA has been detected in
GC while IGF-2 mRNA has been detected in TC (Hammond et al., 1985; Yuan et al., 1996).
Ovarian synthesis of IGFs and their receptors is under hormonal regulation. In cattle,
FSH, LH, cortisol, insulin, and growth hormone (GH) alone and epidermal growth factor
(EGF) or FGF2 together with insulin all decrease GC IGF-1 secretion in vitro (Spicer et al.,
1993; Spicer and Chamberlain, 2000) while cortisol and tumor necrosis factor α (TNFα) decreased IGF-1 receptor synthesis by TC (Spicer and Chamberlain, 1998; Spicer, 2001). In rats, whole ovarian IGF-1 synthesis was decreased by FSH and increased by estrogen, IGF-2 production was decreased by estrogen, and IGF-1 receptor synthesis was increased by FSH
(Hernandez, 1995; Zhou et al., 2013). In pigs, GH, FSH, and estradiol all increased GC IGF-1 secretion in vitro (Hsu and Hammond, 1987). In humans, FSH stimulates IGF-2 gene expression by GC (Baumgarten et al., 2015).
Mitogenic effects of IGFs in ovarian follicular cells are well established. Both ligands bind to IGF-1 receptors to stimulate cell proliferation (Schmid, 1995; Spicer and Aad, 2007).
IGF-1 stimulates proliferation of both GC and TC of cattle (Savion et al., 1981; Spicer et al., 24
1993; Stewart et al., 1995; Gutiérrez et al., 1997), pigs (Baranao and Hammond, 1984; May et al., 1988; May et al., 1992; Kolodziejczyk et al., 2003), and rats (Bley et al., 1992; Duleba et al., 1997; Duleba et al., 1999), and also stimulates proliferation of GC from sheep (Monniaux and Pisselet, 1992), and humans (Bergh et al., 1991; Yong et al., 1992). IGF-2 stimulates proliferation of GC of cattle (Spicer and Aad, 2007), humans (Di Blasio et al., 1994;
Baumgarten et al., 2015), pigs (Baranao and Hammond, 1984), and rats (Adashi et al., 1985;
Duleba et al., 1997).
Effects of IGFs in ovarian steroidogenesis have been extensively studied. In several mammalian species, these polypeptides have been described to amplify gonadotropins effects, stimulating steroidogenesis and steroidogenic enzymes in presence of FSH and LH (Adashi et al., 1991; Spicer and Echternkamp, 1995; Armstrong et al., 1996). In fact, IGF-1 is required for effects of FSH on the steroidogenis through the AKT signaling pathway in humans, mice, and rats GC (Zhou et al., 2013). In cattle, IGF-1 has been reported to enhance FSH-stimulated estradiol and LH-stimulated progesterone production by GC, also enhancing the expression of steroidogenic enzymes such as aromatase (Schams et al., 1988; Spicer et al., 1993; Gutiérrez et al., 1997; Spicer and Chamberlain, 1998; Spicer, 2001; Spicer and Aad, 2007), and to increase LH-stimulated progesterone and androstenedione production by TC (Stewart et al.,
1995; Spicer and Chamberlain, 1998; Spicer, 2001). In pigs, IGF-1 enhances FSH-stimulated estradiol and progesterone production by GC (Baranao and Hammond, 1984; Kolodziejczyk et al., 2003; Ranzenigo et al., 2008). In rats, IGF-1 increases the FSH-supported estradiol and progesterone biosynthesis by GC, the FSH-mediated acquisition of LH receptors by GC, and the LH-stimulated progesterone by TC (Adashi et al., 1986; Adashi et al., 1991; Duleba et al.,
1999; Zhou et al., 2013). In humans and sheep, IGF-1 also has a stimulatory effect in FSH- stimulated estradiol production (Bergh et al., 1991; Armstrong et al., 1996). Similar to IGF-1,
IGF-2 enhances FSH-stimulated estradiol and progesterone biosynthesis and aromatase expression in bovine GC (Spicer and Aad, 2007), FSH-stimulated estradiol and progesterone production by human GC (Devoto et al., 1999; Baumgarten et al., 2015), and FSH-stimulated
25
progesterone production by porcine GC (Baranao and Hammond, 1984). These steroidogenic effects of IGF-2 are believed to be performed through the IGF-1 receptor (Spicer and Aad,
2007). Recently, it was suggested that changes in IGF-2 receptor abundance in GC may regulate ovulation rate in cattle (Aad et al., 2012).
Because of their stimulatory effects on steroidogenesis, IGFs are considered important for follicular selection for dominance in monotocous species such as cattle (Spicer,
2004; Fortune et al., 2004). Although, there are no differences in total IGF intrafollicular concentrations between dominant and subordinate follicles in cattle (Stewart et al., 1996), levels of insulin-like binding proteins (IGFBPs) change during follicular development in various species, including sheep and cattle (Monget et al., 1993; Spicer at al., 2001). The
IGFBPs are important for storage and transportation of IGFs through circulation, being important regulators of the IGFs physiological action (Sara and Hall, 1990; Murphy, 1998). In the ovary, six IGFBPs (IGFBP-1 to IGFBP-6) have been identified in antral follicles of mammals (for reviews, see Spicer and Echternkamp, 1995; Fortune et al., 2004; Spicer,
2004). In cattle, the major forms of IFBPs produced by GC are IGFBP-2, IGFBP-5, and
IGFBP-4 while the major forms produced by TC are IGFBP-3, IGFBP-2, IGFBP-5, and
IGFBP-4 (Chamberlain and Spicer, 2001); in sheep, the major forms produced by GC are
IGFBP-2, IGFBP-5, and IGFBP-1 while TC produces mainly IGFBP-4 and IGFBP-2
(Armstrong et al., 1996); in pigs, GC produce IGFBP -2 to -6 (Leighton et al., 1993). Some
IGFBPs, specifically the low molecular weight IGFBP -2, -4, and -5 are increased in atretic follicles of sheep (Monget et al., 1993), cattle (de la Sota et al., 1996; Stewart et al., 1996;
Spicer et al., 2001; Rivera and Fortune, 2003), mice (Wandji et al., 1998), and humans (San
Roman and Magoffin, 1993; Wright et al., 2002). Moreover, IGFBP -2, -3, -4, and -5 and have inhibitory effects on IGF-stimulated steroidogenesis, binding IGFs and preventing them to bind to their receptors (Ui et al., 1989; Bicsak et al., 1990; Spicer and Chamberlain, 1999;
Wright et al., 2002). Therefore, for follicular dominance to occur, levels of low molecular
IGFBPs need to be reduced, which happens through the action of specific proteases such as
26
pregnancy-associated plasma protein A (Spicer et al., 2001; Rivera et al., 2001; Rivera and
Fortune, 2003; Spicer, 2004).
In summary, the ovarian IGF system (IGF ligands, receptors, and binding proteins) is critical for follicular development and selection for dominance through mitogenic and steroidogenic activity. The bioavailability of IGF ligands, especially IGF-1, is more important than their total concentrations and levels of IGBPs are therefore suppressed in dominant follicles by specific proteases.
3.2 Transforming growth factor β family
The TGF-β superfamily is a large group of more than 35 polypeptides in vertebrates that regulate many aspects of cell proliferation and organogenesis, including development of gonads, heart, bones, and blood vessels. Members of this superfamily include TGF-βs, bone morphogenic proteins (BMPs), growth differentiation factors (GDFs), anti-Müllerian hormone (AMH), activins, and inhibins (for review, see Chang et al., 2002).
Members of the TGF-β superfamily possess homo- or hetero-dimers that bind to and activate two types of transmembrane serine/threonine kinase receptors, which then stimulate downstream regulatory SMAD proteins to migrate from the cytoplasm to the nucleus where they can act as transcriptional regulators. Activins and TGF-βs typically use different signal transduction pathways than BMPs. Activins and TGF-βs will first bind receptor type II, which will then recruit and phosphorylate receptor type I, which will in turn phosphorylate SMAD2 or SMAD3, allowing each to migrate to the nucleus and interact with SMAD4 and transcription factors to stimulate specific target genes; BMPs will bind to either type I or type
II receptor to stimulate formation of a quaternary complex and then type I receptor will be phosphorylated by type II and will phosphorylate SMAD1, SMAD5, or SMAD8, allowing each to translocate to the nucleus to interact with SMAD4 and transcription factors in order to stimulate specific target genes (for reviews, see Heldin et al., 1997; Chang et al., 2002).
27
Many TGF-β superfamily members have been detected in the mammalian ovary, including TGF-α, TGF- β, inhibin, activin, follistatin, BMP-2, BMP-3, BMP-4, BMP-6,
BMP-7, GDF-9, BMP-15, AMH (for reviews, see Ying, 1988; Knight and Glister, 2001;
Durlinger et al., 2002a; Shimazaki et al., 2004; Drummond, 2005; Skinner, 2005; Mazerbourg and Hsueh, 2006). These polypeptides regulate folliculogenesis of various species through paracrine, autocrine, and endocrine actions, playing roles in ovarian steroidogenesis (Ying et al., 1986; Miró et al., 1991; Shukovski et al., 1991; Shimasaki et al., 1999; Campbell et al.,
2012), follicular cell proliferation (Roberts and Skinner, 1991; Glister et al., 2004; Spicer et al., 2008; Kayani et al., 2009), and oocyte maturation (Alak et al., 1998).
3.2.1 Role of TGF-α and TGF- β on folliculogenesis
The 50 amino acid polypeptide TGF-α is structurally similar to epidermal growth factor (EGF) and able to bind to EGF receptors to elicit its effects in a variety of cells, including skin keratinocytes and epithelial cells in the brain, pituitary, and various embryonic tissues (Brachmann et al., 1989). In the ovary, TGF-α mRNA has been detected in rat GC
(Yeh et al., 1993), in bovine TC (Skinner and Coffey, 1988; Lobb and Dorrington, 1992), in human TC (Lobb, 2009), and mainly in porcine GC, although small amounts were also detected in porcine TC (Singh and Armstrong, 1995).
The TGF-β polypeptide is a dimer of 112-amino acid subunits linked by disulfide bonds. In mammals, the family of TGF-β consists of at least four closely related isoforms:
TGF-β1 (commonly referred as simply “TGF-β”), TGF-β2, TGF-β3, and TGF-β4 (for review, see Lyons and Moses, 1990). In the ovary of cattle, TGF-β1 has been detected in oocytes and
GC while TGF-β2 and TGF-β3 have been detected in oocytes, GC, and TC with a stronger intensity than TGF-β1 in preantral and antral follicles (Nilsson et al., 2003). In sheep, TGF-β1 and TGF-β2 are restricted to TC (Juengel et al., 2004) and in humans, TGF-β1 has been detected in GC and TC of antral follicles (Lobb, 2009). In pigs, TC are the main source of
TGF-β1 (May et al., 1996) and in rats, both TGF-β1 and TGF-β2 have been detected in GC
28
(Kim and Schomberg, 1989; Teerds and Dorrington, 1992), TC (Teerds and Dorrington,
1992), and oocytes (Teerds and Dorrington, 1992; Ergin et al., 2008), but the amounts of
TGF-β1 are always greater than TGF-β2 in these cells (Teerds and Dorrington, 1992).
Although recognized for their mitotic effects in many tissues, TGFs have different actions in ovarian follicular cell proliferation according to the species. In cattle, TGFs have contrasting effects on GC proliferation: while TGF-α stimulates proliferation of GC, TGF-β inhibits GC proliferation by paracrine and autocrine actions (Lobb and Dorrington, 1992). In rats, TGF-β stimulates GC proliferation (Saragüeta et al., 2002) whereas both TGF-α and
TGF-β increase TC proliferation (Pehlivan et al., 2001). In pigs, TGF-β has been described to inhibit EGF-stimulated GC proliferation, although the opposite has also been observed under diverse experimental circumstances (May et al., 1988; Mondschein et al., 1988). In humans,
TGF-α stimulates, while TGF-β1 inhibits, GC from small antral follicles (Lobb, 2009).
The effects of TGF-α and TGF-β on steroidogenesis also vary according to the species. In cattle, TGF-α suppresses FSH-stimulated estradiol production by GC while both
TGF-α and TGF-β suppress estradiol-stimulated progesterone production by TC (Roberts and
Skinner, 1991; Legault et al., 1999) and EGF inhibited insulin-induced progesterone and androstenedione production by TC (Spicer and Stewart, 1996). Nevertheless, in the presence of estradiol, TGF-β increases progesterone production by TC, suggesting a distinct role for this polypeptide according to the stage of follicle development in cattle (Roberts and Skinner,
1991). In rats, both TGF-α and TGF-β enhance FSH-stimulated progesterone synthesis by GC
(Yeh et al., 1993; Ke et al., 2004; Chen et al., 2008). In pigs, TGF-α stimulates estradiol production by GC from prepubertal females (Gangrade et al., 1991) whereas TGF-β inhibits
FSH-induced progesterone production by porcine GC (Mondschein et al., 1988). In sheep,
TGF-β suppresses progesterone production by GC (Juengel et al., 2004).
3.2.2 Role of activin, inhibin, and follistatin on folliculogenesis
29
Activins and inhibins are disulphide-linked dimeric glycoproteins: while inhibins are dimers of a α subunit linked to either a α A or a α B subunit to generate inhibin A (α-βA) or inhibin B (β-βB), activins are a result of dimerization of β subunits, which results in three forms of activin known as activin A (βA-βA), activin AB (βA-βB) and activin B (βB-βB).
Follistatins are single chain glycosylated polypeptides rich in cysteine that bind to and suppress the effects of activin (for reviews, see Ying, 1988; Knight and Glister, 2001).
The first recognized role for activins, inhibins, and follistatin in reproduction was their ability to modulate the secretion of FSH from anterior pituitary gonadotropins in vitro.
More specifically, inhibins and follistatin suppress FSH secretion while activins enhance FSH secretion (for reviews, see Ying, 1988; de Kretser and Robertson, 1989; Knight and Glister,
2001). In the 1980s, several groups isolated inhibins, activins, and follistatin from follicular fluid (Robertson et al., 1985; Ling et al., 1986; Ueno et al., 1987) and ovaries of farm animals
(Henderson and Franchimont, 1981; Michel et al., 1989).
In the ovary of cattle, inhibins have been detected in mainly in GC, but also in TC
(Henderson and Franchimont, 1981; Torney et al., 1989; Izadyar et al., 1998), activins have been detected in GC (Izadyar et al., 1998), and follistatin has been detected in GC and oocytes (Izadyar et al., 1998). In rats, inhibins have been detected in GC, TC, and oocytes
(Erickson and Hsueh, 1978; Suzuki et al., 1987; Meunier et al., 1988; Ogawa et al., 1991), and activins and follistatin have been detected mainly in GC (Meunier, 1988; Kogawa et al.,
1991; Nakatani et al., 1991), and follistatin has been detected in GC (Kogawa et al., 1991). In pigs, inhibins and follistatin have been detected in GC (Michel et al., 1989; Lindsell et al.,
1995), and activins have been detected in in GC and TC (Van Den Hurk and Van De Pavert,
2001). In humans, inhibins have been detected in GC (Channing et al., 1984; Yamoto et al.,
1992; Erämaa et al., 1995; Sidis et al., 1998), activins have been detected in GC (Sidis et al.,
1998), and follistatin has been detected in GC and oocytes (Tuuri et al., 1994; Sidis et al.,
1998).
30
Activins, inhibins, and follistatin play a distinct role in folliculogenesis of different species. In cattle, while activins have a suppressive effect on LH-stimulated progesterone production by GC and TC from antral follicles, follistatin increased LH-stimulated progesterone production on the same cell types (Shukovski et al., 1991; Shukovski et al.,
1993), indicating that the actions of activin should be suppressed as the follicle approaches luteinization. In addition, inhibins suppress estradiol production by bovine GC (Jimenez-
Krassel et al., 2003), showing an anti-differentiation action. In rats, activins act to increase responsiveness of GC to FSH, increasing FSH receptor concentrations, aromatase expression, progesterone secretion, estradiol production, and GC proliferation (Xiao et al., 1992; Li et al.,
1995; Miró and Hiller, 1996) while follistatin suppresses activin-stimulated GC proliferation
(Li et al., 1995) and inhibin increases proliferation of GC (Woodruff et al., 1990). In pigs, activin inhibits FSH-stimulated estradiol and progesterone synthesis (Chang et al., 1996). In humans, activin stimulates GC proliferation (Rabinovici et al., 1990), but inhibits FSH- stimulated estradiol and progesterone by GC while inhibin enhances FSH-stimulated estradiol production by GC and LH-stimulated progesterone production by TC (Alak et al., 1998;
Gilling-Simth et al., 1997), and follistatin suppresses activin inhibitory effect on FSH- stimulated estradiol and progesterone synthesis by GC (Cataldo et al., 1994).
3.2.3 Role of oocyte-derived GDF-9, BMP-6, and BMP-15 on folliculogenesis
The communication between oocyte and surrounding somatic cells (GC and TC) is critical for folliculogenesis and it has been suggested that the oocyte carries this conversation
(Matzuk et al., 2002). Among the members of the TGF-β superfamily that regulate ovarian folliculogenesis, GDF-9, BMP-15, and BMP-6 are produced mainly by oocytes (for review, see Elvin et al., 2000). Indeed, GDF-9 mRNA and protein have been detected in the oocyte of primary, secondary and preantral follicles of rat (Hayashi et al., 1999; Jaatinen et al., 1999), in oocytes of human primary follicles (Aaltonen et al., 1999), in oocytes of mice at all stages of follicular development, except in primordial follicles (McGrath et al., 1995; Dube et al.,
1998), and mainly in oocyte, but also in GC, of cattle during all stages of follicular 31
development (Bodensteiner et al., 1999; Spicer et al., 2008). BMP-15, which is structurally related to GDF-9, has a similar localization to GDF-9 in rats (Jaatinen et al., 1999), mice
(Dube et al., 1998), and humans (Aaltonen et al., 1999), but has also been detected in oocytes and GC of antral follicles of rats (Erickson and Shimasaki, 2003) and exclusively in oocytes of bovine antral follicles (Pennetier et al., 2004). BMP-6 has been detected in oocytes of mice
(Lyons et al., 1989) and in TC, GC, and oocytes from antral follicles of cattle (Glister et al.,
2004; Kayani et al., 2009).
Knockout mice models indicate a greater importance for GDF-9 to fertility in comparison to BMP-15 and BMP-6, at least in the murine species: while GDF-9 knockout female mice are completely infertile and have no follicular development beyond the primary one layer follicle stage (Dong et al., 1996), BMP-15 deficient female mice are only subfertile, having reduced ovulation and defects in early follicle development (Yan et al., 2001), and
BMP-6 deficient female mice are fertile (Solloway et al., 1998). Observations that GDF-9 deficient female mice have a limited oocyte development and have an impaired attachment of cumulus cells to the zona pelucida of oocytes may explain why this factor is critical in the early stages of follicular development (Carabatsos et al., 1998), since the communication between the oocyte and surrounding somatic cells is not working properly in this case. In addition, a recent study revealed that GDF9-induced Indian hedgehog homolog (IHH) production by GC is needed for TC development (Liu et al., 2015). Moreover, in later stages of folliculogenesis, GDF-9 stimulates progesterone production and the expression of enzymes involved in cumulus expansion by mice GC (Elvin et al., 1999).
In rats, GDF-9 promotes follicular survival and growth during the preantral to early antral transition, increasing estradiol and testosterone production by GC and therefore suppressing GC apoptosis and follicular atresia (Hayashi et al., 1999; Orisaka et al., 2006;
Orisaka et al., 2009). In later stages, GDF-9 stimulates GC proliferation while it suppresses
FSH-stimulated estradiol and progesterone production by GC from small antral follicles and preovulatory follicles of mice, therefore suppressing GC differentiation (Vitt et al., 2000). 32
BMP-15 also stimulates proliferation of GC from rat antral follicles while it suppresses FSH- stimulated progesterone production with no effects on FSH-stimulated estradiol (Otsuka et al., 2000; Otsuka et al., 2001a; Otsuka and Shimasaki, 2002), therefore acting as an anti- differentiation factor. Different than GDF-9 and BMP-15, BMP-6 does not stimulate mitogenic activity of rat GC, but acts like BMP-15 on steroidogenesis of GC, suppressing
FSH-stimulated progesterone production without affecting estradiol production (Otsuka et al.,
2001b).
In cattle, GDF-9 acts on TC from antral follicles, enhancing LH-stimulated TC proliferation in small follicles, but suppressing LH-stimulated TC proliferation in large follicles in the presence of IGF-1 (Spicer et al., 2008). Also, GDF-9 suppresses IGF-1 stimulation of both androstenedione and progesterone by TC from all sizes of antral follicles
(Spicer et al., 2008). Similarly, GDF-9 stimulates proliferation of GC but inhibits IGF-1- induced steroidogenesis of GC from both small and large follicles of cattle (Spicer et al.,
2006). These studies suggest that GDF-9 is acting as an anti-differentiation factor in cattle.
On the other hand, when added to in vitro maturation medium of bovine cumulus-oocyte complexes, BMP-15 enhanced cumulus expansion, which is important for oocyte competence
(Caixeta et al., 2013). Finally, oocyte-derived BMP-6 stimulates GC proliferation and estradiol production while suppressing progesterone production by both GC and TC from small bovine antral follicles (Glister et al., 2004; Kayani et al., 2009), thereby stimulating follicular survival.
3.2.4 Role of BMPs on folliculogenesis
In addition to BMPs derived from oocyte, BMP-2, BMP-3, BMP-4, and BMP-7 may also regulate the ovarian follicular development of mammals. These polypeptides regulate folliculogenesis of several species through modulation of steroidogenesis and mitosis of follicular ovarian somatic cells (for review, see Shimasaki et al., 2004). Among the BMPs produced by the ovary, BMP-2 has been detected mainly in GC of cattle (Kayani et al., 2009)
33
and rats (Erickson and Shimasaki, 2003), and in oocytes of pigs (Brankin et al., 2005a;
Paradis et al., 2009). BMP-3 has been detected in TC of rats (Erickson and Shimasaki, 2003) and in GC of humans (Jaatinen et al., 1996) whereas BMP-4 has been detected in TC of cattle
(Glister et al., 2004; Kayani et al., 2009) and rats (Shimasaki et al., 1999; Erickson and
Shimasaki, 2003), and in the oocyte and GC of pigs (Zhu et al., 2008). BMP-7 has been detected in TC of cattle (Glister et al., 2004; Kayani et al., 2009) and rats (Shimasaki et al.,
1999; Erickson and Shimazaki, 2003).
In cattle, BMP-2 functions as an autocrine factor during follicular dominance and ovulation in cattle, because it simulates estradiol production by GC and its expression in GC increases as antral follicles grow (Selvaraju et al., 2013). In pigs, BMP-2 suppresses progesterone production by GC and TC without affecting GC or TC proliferation (Brankin et al., 2005a; Brankin et al., 2005b).
Theca-derived BMP-4 and BMP-7 may also alter follicular development by increasing GC proliferation and modulating steroidogenesis. In rats, BMP-4 and BMP-7 increased FSH-stimulated estradiol production while suppressing FSH-stimulated progesterone production by GC (Shimasaki et al., 1999; Lee et al., 2001; Inagaki et al., 2009).
Also in rats, BMP-4 promotes the primordial-to-primary follicle transition in neonatal rat ovaries (Nilsson and Skinner, 2003). In cattle, BMP-4 and BMP-7 inhibit steroidogenesis in
GC (Glister et al., 2004; Spicer et al., 2006; Yamashita et al., 2011) and TC (Glister et al.,
2005; Spicer et al., 2008). In humans, BMP-4 and BMP-7 appear to play a role in atresia, since both polypeptides decrease gap junction intercellular communication activity (Chang et al., 2013) while BMP-4 decreases basal estradiol production by GC (Khalaf et al., 2013).
3.2.5 Role of AMH on folliculogenesis
During fetal development, AMH, also called Müllerian inhibiting substance (MIS), is produced only by Sertoli cells, but ovarian follicles also produce this polypeptide after birth
(Münsterberg and Lovell-Badge, 1991). The main ovarian follicular compartment producing 34
AMH in various species is GC: in cattle, AMH mRNA is expressed in GC of healthy antral follicles (Ireland et al., 2009), and in sheep, AMH mRNA is expressed exclusively in GC from secondary and antral follicles, decreasing as the follicles grow (Campbell et al., 2012).
In mice, AMH protein has been detected in primary and early secondary follicles (Durlinger et al., 2002b), and in rats, AMH mRNA is expressed in GC from preantral and small antral follicles (Baarends et al., 1995). In humans, AMH protein has been detected in secondary, preantral, and small antral follicles (Weenen et al., 2004), and may be a valuable indicator of ovarian reserve in human assisted reproduction (La Marca et al., 2010; Tolikas et al., 2011).
In cattle, AMH is a biomarker for fertility, since GC from cows with high numbers of antral follicles per ovary have a greater AMH expression than those with numbers of antral follicles per ovary (Ireland et al., 2009), and abundance of GC AMH mRNA is greater in healthy than in atretic follicles (Rico et al., 2009). In contrast, knockdown of AMH bioactivity stimulates development of ovine antral follicles, suggesting an inhibitory role for
AMH in modulating the response of both TC and GC to gonadotropins in sheep (Campbell et al., 2012). Furthermore, AMH suppresses FSH-stimulated estradiol production by GC in sheep (Campbell et al., 2012). In mice, AMH reduces numbers of growing primordial follicles (Durlinger et al., 2002) and reduces follicular diameter of preantral follicles in vitro
(Durlinger et al., 2001), suggesting a negative regulation of folliculogenesis in this species. In humans, AMH reduces development of primordial follicles (Carlsoon et al., 2006).
4. Bioinformatics tools for microarray analysis
With the advent of the genome projects, our knowledge of the genomic sequences of humans and other organisms greatly increased (Quackenbush, 2001). Subsequently, a diversity of techniques has been developed to investigate the increasing body of information provided by the knowledge of the genome (Quackenbush, 2001). One of these techniques is cDNA microarray, which allows rapid quantification of expression levels of several genes in parallel (Schena et al., 1995; Schena, 1996).
35
The technology of cDNA microarray consists of reversing mRNA into cDNA labeled with fluorescent nucleotides, which then gets hybridized to a microarray under a glass cover slip and scanned for fluorescein emission following laser excitation (Schena et al., 1995;
Schena, 1996). Differential expression measurements are carried out using a simultaneous, two-color hybridization approach of two biological samples of interest, which are mixed and hybridized to a single microarray for posterior scanning at two wave-lengths following independent excitation of the two fluors (Schena et al., 1995; Schena, 1996). Measurement of fluorescence intensity through scanning allows quantification of gene expression and, therefore, the direct comparison of gene expression levels between the samples (Schena et al.,
1995; Schena, 1996; Quackenbush, 2001).
Identifying the various patterns in which a gene is expressed in a microarray and grouping genes into expression clusters provide clues into their biological function (Schena et al., 1995; Quackenbush, 2001). Nevertheless, interpretation of microarray expression data is not an exact science and can be quite challenging (Bowtell, 1999; Quackenbush, 2001; Khatri and Draghici, 2005; Huang et al., 2009; Henderson-MacLennan et al., 2010). Therefore, bioinformatics tools have becoming increasingly important as the technology for microarray- based genomic profiling has been progressing (Eisen et al., 1988; Bowtell, 1999;
Subramanian et al., 2005; Capriotti et al., 2012).
Over the last few decades, bioinformatics approaches made it possible to find genes of pertinent biological functions among large lists of genes (Huang et al., 2009; Capriotti et al., 2012). In order to help researchers to find genes of interest in large lists, various high- throughput enrichment tools, including Onto-Express, GoMiner, and Database for
Annotation, Visualization, and Integrated Discovery (DAVID), among many others, were developed (Khatri and Draghici, 2005; Huang et al., 2009). These bioinformatics enrichment tools identify groups of genes that share common biological function, chromosomal location, or regulatory elements (Subramanian et al., 2005; Huang et al., 2009). The theory behind this method is that clusters of genes with a common biological process, regulation, or at the same 36
chromosomal location (based on prior knowledge), should have an enriched potential as a relevant group by the high-throughput screening technologies (Subramanian et al., 2005;
Huang et al., 2009). Therefore, instead of just comparing individual genes that were up- or down- regulated by a treatment or condition, bioinformatics enrichment tools give the researcher an opportunity to visualize how genes are being affected in a more global and logical manner.
The importance of enrichment tools such as DAVID can be observed in microarray research using Affymetrix gene chips to unveil altered biological functions in response to a pathological condition or a hormonal treatment, categorizing clusters of differentially expressed transcripts. For example, in farm animals, DAVID was used for identifying biological functions altered by IGF-1 treatment in cultured porcine GC (Grado-Ahuir et al.,
2009) or to detect functional differences between bovine GC extracted from healthy or cystic antral follicles (Grado-Ahuir et al., 2009), providing valuable data to improve reproductive efficiency in pigs and cattle. Moreover, DAVID can be used to investigate biological functions altered by pathologies such as human prostatic cancer (Rowehl et al., 2008) or diabetic nephropathy (Cohen et al., 2008), providing a better understanding of causes and consequences of human diseases and contributing to a possible improvement in therapy efficiency.
Other valuable bioinformatics tool for the interpretation and management of large- scale genetic data sets is the pathway analysis software. Since biological processes commonly involve more than one pathway, this tool identifies networks of pathways altered by a treatment, biological condition, or different time points, allowing identification of biological functions and canonical signaling pathways, determining the enrichment of differentially expressed genes within groups of interconnected pathways and contributing to provide meaning to identified differences in gene expression (Werner, 2008; Henderson-MacLennan et al., 2010). Examples of pathway analysis software are Ingenuity Pathway Analysis (IPA),
37
GeneGo, BioBase, Genomatix, and Pathway Studio (Werner, 2008; Henderson-MacLennan et al., 2010).
The web-based pathway analysis software IPA facilitates a meaningful interpretation of data by allowing the identification of canonical pathways, mechanistic networks, upstream regulators, and downstream biological functions affected by diseases, treatments, or different time points (Krämer et al., 2013). Examples of the use of this software include the investigation of bovine ovarian follicular activation (Yang and Fortune, 2015), bovine oocyte maturation (Mamo et al., 2011), differences between ovarian follicular somatic cells
(Hatzirodos et al., 2014a; 2014b) of healthy or atretic bovine antral follicles, and differences between microRNAs expression pattern in bovine GC of dominant or subordinate follicles
(Wondim et al., 2014), which shows how the use of this bioinformatics tool has been emerging to help researchers to understand biological processes such as ovarian folliculogenesis.
38
Table 1. Characterization of FGFs subfamilies and their secretion from the cells.
FGF Subfamily Signal peptide and secretion
FGF 1/ 2 Lack cleavable signal peptide, but are still secreted through non- conventional mechanisms FGF 3/7/10/22 Have N-terminal signal peptide and are secreted through classical mechanisms FGF 4/5/6 Have N-terminal signal peptide and are secreted through classical mechanisms FGF 8/17/18 Have N-terminal signal peptide and are secreted through classical mechanisms FGF 9/16/20 Lack cleavable signal peptide, but are still secreted through non- conventional mechanisms FGF 11/12/13/14 Lack signal peptide and remain inside the cell
FGF 15/19/21/23 Have N-terminal signal peptide and are secreted through classical mechanisms
Adapted from: Itoh and Ornitz (2011); Li et al. (2016).
39
Table 2. Receptor affinities for different FGFs subfamilies.
FGF Subfamily Receptor affinity
FGF 1/ 2 FGFR 1c, 3c > 2c, 1b, 4
FGF 3/7/10/22 FGFR 2b > 1b
FGF 4/5/6 FGFR 1c, 2c > 3c, 4
FGF 8/17/18 FGFR 3c > 4 > 2c > 1c > 3b
FGF 9/16/20 FGFR 3c > 2c > 1c, 3b > 4
FGF 11/12/13/14 Do not bind to FGFRs
FGF 15/19 FGFR 1c, 2c, 3c, 4 FGF 21 FGFR 1c, 3c FGF 23 FGFR 1c, 3c, 4
Adapted from: Ornitz and Itoh (2015).
40
5. References
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regulating selection of 2 dominant follicles in cattle selected for twin ovulations and
births. Domest. Anim. Endocrinol. 45: 187-195.
Aad, P. Y., S. E. Echternkamp, D. D. Sypherd, N. B. Schreiber, and L. J. Spicer. 2012. The
hedgehog system in ovarian follicles of cattle selected for twin ovulations and births:
Evidence of a link between the IGF and hedgehog systems. Biol. Reprod. 87: 1-10.
Aaltonen, J., M. P. Laitinen, K. Vuojolainen, R. Jaatinen, N. Horelli-Kuitunen, L. Seppa, H.
Louhio, T. Tuuri, J. Sjoberg, R. Butzow, O. Hovatta, L. Dale, and O. Ritvos. 1999.
Human growth differentiation factor 9 (GDF-9) and its novel homolog GDF-9b are
expressed in oocytes during early folliculogenesis. J. Clin. Endocrinol. Metab. 84:
2744-2750.
Abraham, J. A., A. Mergia, J. L. Whang, A. Tumolo, J. Friedman, K. A. Hjerrild, D.
Gospodarowicz, and J. C. Fiddes. 1986. Nucleotide-sequence of a bovine clone
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CHAPTER III
CHANGES IN FIBROBLAST GROWTH FACTOR 9 (FGF9) mRNA IN GRANULOSA AND THECA CELLS DURING OVARIAN FOLLICULAR GROWTH IN DAIRY CATTLE
1. Abstract
Fibroblast growth factor 9 (FGF9) has been suggested to act as an anti-differentiation factor in cattle by reducing steroidogenesis and increasing cell proliferation in granulosa (GC) and theca (TC) cells. The objective of this study was to characterize FGF9 mRNA abundance in GC and TC during development of dominant follicles in dairy cattle. Estrous cycles of non- lactating dairy cattle were synchronized, and ovaries were collected on either day 3-4 (n = 8) or day 5-6 (n = 8) post-ovulation for GC and TC mRNA extraction from small (1-5 mm), medium (5.1-8 mm) or large (8.1-18 mm) follicles for PCR analysis. FGF9 mRNA abundance was greater (P < 0.05) in GC than in TC. In GC, FGF9 mRNA abundance was greater (P < 0.05) in small, medium and large estrogen (E2)-inactive (i.e., concentrations of
E2 < progesterone, P4) follicles than in large E2-active (i.e., concentrations of E2 > P4) follicles at both early (day 3-4) and late (day 5-6) growing phases of first dominant follicle.
Abundance of FGF9 mRNA was greater (P < 0.05) in medium-sized follicles on day 5-6 than on day 3-4 post-ovulation. In TC, FGF9 mRNA abundance was greater (P < 0.05) in large
E2-inactive follicles than in large E2-active follicles on day 3-4 post-ovulation; no significant differences in TC FGF9 mRNA existed among follicle types on day 5-6 post-ovulation.
Correlations among levels of hormones and FGF9 mRNA levels revealed significant negative correlations between GC FGF9 mRNA abundance and follicular fluid E2 (r = -0.68), E2/P4 ratio (r = -0.58), and free insulin-like growth factor 1 (r = - 0.63). In summary, abundance of
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FGF9 mRNA in GC and TC is greater in medium-sized follicles at late than at early growing phase of first dominant follicle, and is less in dominant E2-active than subordinate E2- inactive follicles, indicating that FGF9 signaling could contribute to normal follicle development and steroidogenesis in dairy cattle.
Key Words: Fibroblast growth factor-9 (FGF9), theca cell, granulosa cell, follicle growth, cattle.
2. Introduction
Fibroblast growth factors (FGFs) constitute a large family of polypeptide growth factors present in both vertebrates and invertebrates (Ornitz and Itoh, 2001). These growth factors and their receptors are distributed in various tissues and regulate development, metabolism and disease through intracrine, paracrine and endocrine mechanisms of action
(Itoh and Ornitz, 2011). FGF family members have also been identified to play important roles in the reproduction of mammals including the human, caprine, ovine, bovine and murine species (for review see Chaves et al., 2012). To date, FGF1, FGF2, FGF7-9, FGF10, FGF17 and FGF18 have been identified in the ovary of humans (Oron et al., 2012), rodents
(Drummond et al., 2007), and/or domestic animals (Berisha et al., 2004; Machado et al.,
2009; Portela et al., 2010). Functions of FGF members in the ovary include regulation of granulosa cell (GC) steroidogenesis of cattle and pigs (Vernon and Spicer, 1994; Schreiber and Spicer, 2012; Evans et al., 2014), regulation of GC apoptosis and survival in rats (Tilly et al., 1992; Peluso et al., 2001) and cattle (Portela et al., 2010; Jiang and Price, 2012), control of bovine GC proliferation and differentiation (Berisha et al., 2004; Schreiber and Spicer,
2012), oocyte maturation in rats and cattle (LaPolt et al., 1990; Cho et al., 2008), and luteal development in cattle (Gabler et al., 2004; Woad et al., 2012).
Abundance of FGF9 mRNA was first observed to be down-regulated in GC of cystic follicles of cattle compared with noncystic follicles in a microarray study, indicating that
FGF9 may play a role in bovine follicular development (Grado-Ahuir et al., 2011). 92
Subsequently, abundance of FGF9 mRNA was found to be greater in GC than in theca cells
(TC) and greater in both GC and TC in small follicles (i.e., 1-5 mm) in comparison to large
(i.e., ≥ 8 mm) follicles (Schreiber et al., 2012). Hormones known to be involved in follicular development (e.g., insulin-like growth factor 1; IGF1) also regulate FGF9 mRNA in both GC
(Schreiber and Spicer, 2012) and TC (Schreiber et al., 2012). Furthermore, FGF9 treatment stimulated bovine GC and TC proliferation while down-regulating hormone-stimulated steroidogenesis and steroidogenic enzyme gene expression, indicating a role for FGF9 as an anti-differentiation factor regulating folliculogenesis (Schreiber and Spicer, 2012; Schreiber et al., 2012). Increased free IGF1 may amplify FSH-induced estradiol (E2) production in the developing dominant follicle of cattle (Spicer, 2004). However, whether endogenous production of FGF9 by ovarian follicular cells changes during selection of dominant follicles in monotocous mammals such as cattle is still unknown. We hypothesized that FGF9 mRNA decreases as follicles grow and differentiate. Therefore, the objective of this study was to determine if abundance of FGF9 mRNA in GC and TC changes during growth of first-wave dominant follicles in dairy cattle exhibiting regular estrous cycles.
3. Materials and Methods
Animals and Experimental Design
Non-lactating Holstein cows (n = 18) were used for this experiment as previously described (Dentis et al., 2016). Briefly, estrous cycles were synchronized using two injections
(im) of PGF2α (Lutalyse®, 25 mg) with an interval of 11 days. From the first injection of prostaglandin F2α to the occurrence of ovulation after the second injection, follicle development was monitored daily via ultrasonography using an Aloka 500V with a 7.5 MHz probe. Following ovulation, cows continued to be monitored with daily ultrasonography and were assigned to be ovariectomized either at d 3 to 4 (early growing phase of the first dominant follicle; n = 9 cows) or d 5 to 6 (late growing phase of the first dominant follicle; n
= 9 cows). From the 18 cows used in the synchronization program, two failed (one from day 3
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to 4 post-ovulation and one from day 5 to 6 post-ovulation groups) to ovulate and were excluded from this experiment. After each ovariectomy, ovaries were put on ice, and transported to the laboratory where diameters of all follicles ≥ 5 mm (surface diameter) in diameter were recorded, the numbers of all follicles ≥ 1 mm in diameter on the ovarian surface determined, and ovarian tissue and fluid collected (Dentis et al., 2016). The animal experimentation described in this report was approved by the Oklahoma State University
Institutional Animal Care and Use Committee (Protocol No. AG106).
Cell and Follicular Fluid Collection
For GC sample collection, follicles were categorized by surface diameter as small (1-
5 mm), medium (5.1-8 mm) or large (8.1-18 mm); TC samples were collected from only medium and large follicles. Follicular fluid (FFL) from medium and large follicles was aspirated individually and centrifuged to obtain GC; FFL from small follicles was pooled within each ovary and then centrifuged at 200 x g for 8 min to obtain GC as previously described (Stewart et al., 1996; Dentis et al., 2016). After centrifugation, FFL was aspirated and stored at -20 °C for measurement of E2 and progesterone (P4) via RIA. After collection of FFL, each medium and large follicle was bisected in situ, the inner wall was scraped, rinsed with Ham’s F-12 to remove any remaining GC, and these GC were combined with GC collected from FFL as previously described (Schreiber and Spicer, 2012; Dentis et al., 2016).
GC collected from small follicles were kept separate for each ovary. GC were lysed in 0.5 mL of TRIzol® reagent solution (Life Technologies, Inc., Grand Island, NY) and stored frozen at
-80 °C until RNA extraction (see description below). TC were dissected from the bisected follicles and placed in 0.75 mL of TRIzol® reagent solution and homogenized for 2-3 min on ice using the Omni TH tissue homogenizer (Omni International Inc., Marietta, GA) with
Omni Tip™ disposable generator probes as previously described (Aad et al., 2012; Aad et al.,
2013).
RNA Extraction and Quantitative PCR (qPCR)
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RNA was extracted from GC and TC as described elsewhere (Lagaly et al., 2008).
Phase Lock GelTM (5 Prime, Inc., Gaithersburg, MD) tubes were used to aid in the recovery of aqueous phase containing RNA. RNA samples were solubilized in diethylpyrocarbonate- treated water (Life Technologies, Inc.), quantified at 260 nm using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies Inc., Wilmington, DE), and stored at -80 °C.
FGF9 primers and probe (supplied as 5’ FAM reporter dye and a 3’ TAMRA quencher dye; TaqMan TAMARA; Applied Biosystems Inc., Foster City, CA) for qPCR were designed using Primer Express software (Foster City, CA) as previously reported (Grado-
Ahuir et al., 2011; Schreiber and Spicer, 2012). The FGF9 mRNA (697 bp; Accession
NM_001245926.1) forward primer was constructed between bp 387 and 408 with a Tm of
58°C and a sequence of 5’-TCTACCTCGGCATGAATGAGAA-3’. The reverse FGF9 mRNA primer was constructed between bp 476 and 497 with a Tm of 57°C and a sequence of
5’- TGGAGGAGTACGTGTTGTACCA-3’. The FGF9 mRNA probe was constructed between bp 421 and 444 with a Tm of 66°C and a sequence of 5’-
TGGATCGGAAAAACTCACGCAAGA-3’. Relative mRNA abundance of target genes was quantified using fluorescent single-step qPCR using an ABI Prism® 7500 sequence detection system (Applied Biosystems). Target gene expression was normalized to constitutively expressed 18S ribosomal RNA (18S rRNA; supplied as a VIC probe; TaqMan Ribosomal
RNA Control Reagent, Applied Biosystems Inc.), which has been reported as a valid housekeeping gene for bovine GC and TC (Voge et al., 2004), and relative quantity of target gene mRNAs was expressed as 2-ΔΔCt using the relative comparative threshold cycle (Ct) method as previously described (Livak and Schmittgen, 2001; Lagaly et al., 2008).
Radioimmunoassays (RIA) and IGF1 ELISA
Concentrations of P4 and E2 in FFL were determined by RIA as previously described
(Stewart et al., 1996; Dentis et al., 2016). All samples were run in one assay for each of the
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steroid RIA. The intra-assay coefficient of variation for P4 and E2 RIA averaged 11.6 % and
10.6 %, respectively.
Free IGF1 concentrations in FFL were determined in a subset of samples (n = 32) via a free IGF1 ELISA kit (R&D Systems, Minneapolis, MN) according to the manufacturer’s protocol similar to previously described (Santiago et al., 2005; Spicer et al., 2005). If sample values were below the limit of detection of the assay, a 0.2 ng/mL value was assigned to that sample. All samples were quantified in one assay and the intra-assay coefficient of variation averaged 6.9 %.
FGF9 Western Blotting
Western blotting was utilized in an attempt to detect FGF9 protein in FFL. Protease inhibitor cocktail for use with mammalian cell and tissue extracts (Sigma-Aldrich, St Louis,
MO) at 1:30 and sample buffer (tris-hydrochloride buffer, 10% SDS, glycerol, bromophenol blue, and β–mercaptoethanol) at 1:3 were added to FFL samples. Recombinant human FGF9
(R&D systems Inc., Minneapolis, MN) was added to FFL (at a total amount of 2.5 ng) and
PBS (at total amounts of 5 ng, 1 ng, and 0.1 ng) samples for evaluation of sensitivity of detection. Samples were boiled for 5 min, cooled down, centrifuged at 2000 x g for 1 min, and loaded into 4% stacking, 12% resolving SDS-PAGE mini gels. Precision Plus Protein™
Kaleidoscope™ Standards (Bio-Rad Laboratories, Inc., Hercules, CA) were added for monitoring electrophoretic separation and molecular weight sizing. Gels were ran at 120 V, for 80 min. Gels were transferred to nitrocellulose membranes via iBlot® Gel Transfer
Device (Life Technologies, Inc., Carlsbad, California). After transfer, the nitrocellulose membranes were blocked in Tris-buffered saline (TBS) containing 5% (w/v) nonfat dry milk for 1 h at room temperature and then incubated with a FGF9 antibody (rabbit polyclonal antibody against human FGF9; Santa Cruz Biotechnology, Inc., Dallas, TX) at 1:250 overnight at 4oC. Membranes were washed with a mixture of Tris-buffered saline and Tween
20 (TBST) and incubated with secondary HRP-conjugated antibody (ImmunoPure HRP-
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conjugated goat anti-rabbit IgG, Pierce Biotechnology, Rockford, IL) diluted in TBS containing 5% (w/v) nonfat dry milk at 1:50,000 for 1 h at room temperature on a rocking platform shaker. Membranes were then washed again with TBST, dried, and incubated with enhanced chemiluminescent (ECL) substrate (SuperSignalTM West Femto maximum sensitivity substrate; Thermo Fisher Scientific, Inc., Waltham, MA) for 5 min at room temperature. Finally, membranes were developed via the FluorChemTM E system Imager
(ProteinSimple; San Jose, CA) on movie mode for 180 min chemiluminescence detection.
Statistical Analyses
The analysis of data aimed to determine if FGF9 mRNA abundance differs in GC and
TC at different periods of follicular development and to detect its relationship with steroidogenesis. Data were analyzed via factorial ANOVA with GLM procedures of SAS for
Windows (version 9.2, SAS Institute Inc., Cary, NC) and are presented as the least squares means (± SEM) of measurements. Main factors were days post-ovulation (early, day 3-4, and late, day 5-6, growing phase of the first dominant follicle), and follicle status based on size and follicle estrogenic status [large E2 active (E2>P4 concentrations), and small, medium, or large E2 inactive (E2 FFL samples were lost during collection, then E2-status could not be determined and gene expression data was not included in the analysis. For analysis of E2 and free IGF1 concentrations in the subset of FFL samples, main factors were days post-ovulation (early, day 3-4, and late, day 5-6, growing phase of the first dominant follicle), follicle status (n = 3) based on size (small EI, large EA or large EI) and their various interaction. To correct for heterogeneity of variance, abundance of FGF9 mRNA was analyzed after transformation to natural log (x + 1). Mean differences were determined by Fisher’s protected least significant differences test (Ott, 1977) only if significant main effects in the ANOVA were detected. To evaluate the relationships among variables measured, Pearson correlation coefficients were 97 generated using CORR procedure of SAS (SAS Institute). Significance was declared at P < 0.05. 4. Results GC FGF9 mRNA Abundance Averaged across follicle size groups, qPCR results indicated that FGF9 mRNA abundance in GC was 6.2-fold greater (P < 0.05) than in TC, and that GC FGF9 mRNA abundance was 2.9-fold greater (P < 0.05) at late (day 5-6 post-ovulation) than at early (day 3-4 post-ovulation) growing phase of the first dominant follicle (145 ± 46 and 49 ± 7, respectively). Abundance of FGF9 mRNA was greater (P < 0.01) in large, medium, and small E2-inactive (E2/P4 ratio < 1) than in large E2-active (E2/P4 ratio > 1) follicles at both early (19-, 27- and 18-fold greater, respectively) and late (35-, 77- and 32-fold greater, respectively) growing phases of first dominant follicle (Figure 1A). Also, when E2-inactive follicles of same size were compared at different days post-ovulation, FGF9 mRNA abundance was 3.7-fold greater (P < 0.01) in medium-sized follicles at late than at early growing phase of the first dominant follicle while no significant differences were detected between large or small E2-inactive follicles (Figure 1A). Abundance of FGF9 mRNA in GC was 2.2–fold greater (P < 0.01) in E2-inactive medium- and small-sized follicles than in E2- inactive large-sized follicles at late growing phase (day 5-6) of the first dominant follicle, with no significant differences observed between other sizes at this phase or between any of the E2-inactive follicle sizes at day 3-4 post-ovulation (Figure 1A). Averaged across days, FGF9 mRNA abundance in GC was several-fold greater (P < 0.01) in large (70.6 ± 14.1), medium (179.6 ± 38.6), and small (90.5 ± 21.1) E2-inactive than in large E2-active follicles (5.1 ± 1.0). TC FGF9 mRNA Abundance 98 No significant interaction existed between days post-ovulation and follicle status for TC FGF9 mRNA abundance. In contrast to what was observed in GC, averaged across follicle size groups there was a tendency (P = 0.05) for TC FGF9 mRNA abundance to be greater in early (2.7 ± 3.1) than in late (1.6 ± 0.7) growing phase of the first dominant follicle. Abundance of FGF9 mRNA in TC was 2.2-fold greater (P < 0.05) in large subordinate E2- inactive follicles than in large dominant E2-active follicles on day 3-4 post-ovulation (Figure 1B). No other significant differences were detected between subordinate E2-inactive and large dominant E2-active follicles on day 5-6 post-ovulation, or between large E2-inactive follicles and medium E2-inactive follicles. Abundance of FGF9 mRNA in TC was greater in large subordinate E2-inactive follicles at day 3-4 than at day 5-6 post-ovulation, whereas no significant changes were observed in the other two groups of follicles (Figure 1B). Follicle Size, E2, P4 and Free IGF1 Concentrations in Follicular Fluid Follicle size and steroid concentrations in FFL have been reported for this study (Dentis et al., 2016). Briefly, diameter of large dominant E2-active, large subordinate E2- inactive, and medium E2-inactive follicles averaged 12.9 ± 0.5, 9.48 ± 0.36, and 6.37 ± 0.23 mm, respectively. Concentrations of E2 in FFL of large dominant E2-active, large subordinate E2-inactive, medium E2-inactive, and small E2-inactive follicles averaged 186.5 ± 29.5, 8.45 ± 3.7, 2.3 ± 0.8, and 2.0 ± 0.2 ng/ml, respectively. Concentrations of P4 in FFL did not differ (P > 0.10) among follicle groups and ranged between 61 ± 7 and 236 ± 42 ng/ml. In a subset of these samples (n=32) representative of a range of steroid levels, concentrations of E2, P4 and free IGF1 in large dominant E2-active, large subordinate E2- inactive, and small E2-inactive follicles are shown in Figure 2. Large dominant E2-active follicles had greater (P < 0.05) free IGF1 (Figure 2A) and E2 (Figure 2B) but tended to have less (P < 0.10) P4 (Figure 2B) than large E2-inactive and small E2-inactive follicles. 99 Concentrations of free IGF1, E2 and P4 in large E2-inactive and small E2-inactive follicles did not differ (P > 0.10). Correlations between FFL Concentrations of Hormones and FGF9 mRNA Relative Abundance Negative correlations existed between GC FGF9 mRNA abundance and FFL E2 (r = - 0.68, P < 0.001; Figure 3) and E2/P4 ratio (r = -0.58, P < 0.001; n = 140). In contrast, there was a weak positive correlation (r = 0.18, P < 0.05) between GC FGF9 mRNA abundance and FFL P4. No significant correlation was observed between TC FGF9 mRNA abundance and FFL P4 (r = 0.06, P > .50), but there was a weak negative correlation between TC FGF9 mRNA abundance and FFL E2 (r = -.26, P < 0.05) and E2/P4 ratio (r = - 0.22, P = 0.05; n = 88). Free IGF1 concentrations in FFL and GC FGF9 mRNA abundance were negatively correlated (r = -0.63, P < 0.001; n = 32), whereas free IGF1 concentrations and E2 concentrations in FFL were positively correlated (r = 0.85, P < 0.001). There was no significant correlation between FFL concentrations of P4 and free IGF1 (r = -0.19, P > 0.10). The E2/P4 ratio was positively correlated with free IGF1 in FFL (r = 0.63, P < 0.001). FGF9 Protein in FFL Recombinant human FGF9 protein was detected via Western blotting at total amounts of 5 ng and 1 ng in 15 µL of PBS and 5 µL of sample buffer, and at a total amount of 2.5 ng in 5 µL FFL, 10 µL of PBS, and 5 µL of sample buffer (i.e., an equivalent sensitivity of 125 ng/mL of FFL). The sensitivity of the antibody, however, was not adequate to detect recombinant human FGF9 protein at a total amount of 0.1 ng in 15 µL of PBS and 5 µL of sample buffer or to detect endogenous FGF9 protein in either 10 µL of FFL, 5 µL of PBS, and 5 µL of sample buffer, or 5 µL of FFL, 10 µL of PBS, and 5 µL of sample buffer (Figure 4). 5. Discussion 100 FGF9 has been characterized as an anti-differentiation factor in folliculogenesis of cattle, stimulating both GC and TC proliferation while inhibiting steroidogenesis (Schreiber and Spicer, 2012; Schreiber et al., 2012). In the present study, we report for the first time that FGF9 mRNA abundance in GC and TC changes according to E2 activity and size of follicles, and also during follicle development in cattle. In the present study, follicles were collected at specific days of a synchronized cycle during the first follicular wave and thus represent a well-defined physiologic model. Consistent with what is expected from a factor that stimulates cells to proliferate while inhibiting their differentiation by decreasing E2 production (as described in Schreiber and Spicer, 2012), the abundance of FGF9 mRNA in GC was less in large dominant E2-active follicles at early and late growing phases of the first follicular wave than in subordinate E2- inactive follicles of various sizes, indicating that FGF9 production likely decreases as the follicle becomes dominant and increased steroidogenesis is required for its further differentiation. In support of this latter suggestion, FFL E2 concentrations and E2:P4 ratio were negatively correlated with GC FGF9 mRNA abundance in the present study. Alternatively, increased E2 may directly inhibit FGF9 mRNA expression in GC, but this is unlikely because in vivo, diethylstilbesterol (DES) treatment had no significant effect on ovarian FGF9 mRNA expression in rats (Drummond et al., 2007), and in vitro, E2 had no significant effect on bovine GC FGF9 mRNA abundance (Schreiber and Spicer, 2012). The absence of any change in FFL P4 concentrations during significant changes in both GC and TC FGF9 mRNA indicates that P4 likely does not regulate FGF9 mRNA. Also in the present study, GC FGF9 mRNA increased in medium E2-inactive follicles as the follicular wave advanced from early to late in the growing phase of the first dominant follicle resulting in a greater abundance of FGF9 mRNA in medium than in large-sized follicles at day 5-6 post- ovulation. Perhaps FGF9 is important to assure that only one follicle will differentiate and dominate at the end of the first follicular wave in a monovulatory species such as the bovine. Previous studies in cattle found a greater abundance of FGF18 mRNA in GC and TC of 101 subordinate versus dominant follicles (Portela et al., 2010), and a greater abundance of FGF2 mRNA (Berisha et al., 2004) and FGF10 mRNA (Buratini et al., 2007) in TC of estrogenic versus non-estrogenic antral follicles. In contrast, FGF1 and FGF7 mRNA abundance in GC and TC do not change during follicular development in cattle (Berisha et al., 2004) or pigs (Schams et al., 2009). Collectively, the previous and present studies indicate different developmental control of the various FGFs in GC and TC of follicles during folliculogenesis. As mentioned, E2 does not directly affect FGF9 mRNA abundance in GC (Schreiber and Spicer, 2012), suggesting that one or more hormone(s) or intraovarian factor(s) other than E2 is(are) the cause for lower abundance of FGF9 mRNA in GC of large dominant EA follicles. One of these other intraovarian factors may be IGF1 because IGF1 decreases abundance of FGF9 mRNA in GC from both small and large follicles (Schreiber and Spicer, 2012), and concentrations of free IGF1 in FFL increase in early dominant follicles (Fortune et al., 2001; Spicer, 2004) as well as in preovulatory dominant follicles (Santiago et al., 2005) in cattle. Also, the fact that IGF-1 suppresses Indian hedgehog production in TC (Spicer et al., 2009) and that sonic hedgehog (SHH) stimulates FGF9 production in the ovary (Schreiber and Spicer, 2012) and other tissues (Sun et al., 2000) indicate that hedgehog proteins may be important in FGF9 signaling in the ovary (Figure 5). In addition, we observed that wingless- type mouse mammary tumor virus integration site (WNT)-3A protein inhibited GC FGF9 mRNA (Schreiber and Spicer, 2012). WNTs are secreted ligands that bind to frizzled (FZD) receptor proteins and subsequently transmit their intracellular signals (Grado-Ahuir et al., 2011; Castanon et al., 2012). Recent findings indicate that GC of dominant follicles have greater FZD6 mRNA than subordinate follicles (Gupta et al., 2014) and that FSH increases mRNA abundance of one of FZD6 ligands, WNT2, in bovine granulosa cells (Castanon et al., 2012). Thus, we hypothesize that during dominant follicle development, increases in free IGF1 (Fortune et al., 2001; Spicer, 2004) and WNT signaling (Gupta et al., 2014) cause a decrease in GC FGF9 mRNA (Figure 5). Further research will be required to verify this suggestion. 102 Similar to what was found for GC, there was a negative correlation between TC FGF9 mRNA and E2/P4 ratio in FFL. Also, TC of large E2-inactive follicles had greater abundance of FGF9 mRNA than large E2-active follicles, but only at day 3-4 post-ovulation. Hormones that regulate TC FGF9 mRNA abundance have not been studied in any detail. Interestingly, factors (i.e., TNFα and WNT3A) that inhibit FGF9 mRNA in GC (Schreiber and Spicer, 2012) and inhibit androstenedione production by TC (Spicer, 1998) were found to stimulate FGF9 mRNA in TC (Schreiber et al., 2012). We further hypothesize that IGF1 and WNTs may act in a negative feedback loop within TC promoting FGF9 production to avoid premature differentiation of dominant follicles. Consistent with an opposing regulation of FGF9 mRNA in TC versus GC is the general trend that FGF9 mRNA was greater in TC and lower in GC at day 3-4 in comparison to day 5-6 post-ovulation in the present study. Further work will be required to elucidate the hormonal and developmental control of TC FGF9 mRNA. In the present study, regardless of follicle size, FGF9 mRNA abundance was greater in GC than in TC; this is in agreement with a previous study (Schreiber et al., 2012) and indicates that GC is the main cell type responsible for ovarian follicle production of FGF9. Also, abundance of FGF9 mRNA in GC varied more dramatically with follicle status than in TC, further suggesting a greater importance for GC in FGF9 production during folliculogenesis in cattle. Unfortunately, the two commercial ELISA kits available to measure FGF9 protein (i.e., bovine FGF9 ELISA, NovateinBio, Inc., Cambridge, MA; human FGF9 ELISA, R&D Systems, Minneapolis, MN) did not have adequate sensitivity to detect FGF9 protein in bovine FFL in the present study (Spicer and Schütz, unpublished results). Furthermore, attempts to use Western blotting to detect FGF9 in FFL were unsuccessful, most likely because of the small quantities of protein produced. Sensitivity of detection was 50 ng/mL in PBS and 125 ng/mL in FFL. Based on in vitro studies with half maximal inhibitory concentrations of FGF9 ranging between 2 and 12 ng/mL (Schreiber and Spicer, 2012; Schreiber et al., 2012), FGF9 concentrations in FFL would be near this range. Thus, an 103 estimation of sensitivity of Western blotting system would need to be increased by 5- to 50- fold. Additional developmental work will be required to ascertain changes in FFL FGF9 protein levels during follicular growth and atresia. In summary, FGF9 mRNA abundance in both GC and TC changed during development of dominant and subordinate follicles in cattle. Abundance of FGF9 mRNA was greater in GC than in TC and the more dramatic change in FGF9 mRNA in GC vs. TC indicate a greater importance for GC in ovarian FGF9 production during folliculogenesis in cattle. Dramatically less FGF9 mRNA abundance in dominant E2-active follicles than in E2- inactive subordinate follicles is consistent with what is expected from an anti-differentiation factor. We postulate, as a framework for future studies and based on the experimental data presented in this paper, that FGF9 may play a role in follicular growth and atresia in cattle. Acknowledgments The authors thank Jeff Williams for his laboratory assistance; David Jones, Jeff Davis and other members of the OSU Dairy Cattle Center for care and management of the cows; the OSU Microarray Core Facility and OSU Recombinant DNA/Protein Resource Facility for use of equipment; This work supported in part by: the NICHD, National Institutes of Health, through Agreement R15-HD-066302, and the Oklahoma State University Agricultural Experiment Station. 104 Fig. 1. Abundance of FGF9 mRNA in granulosa and theca cells during follicular growth. Panel A: Effects of follicular size (Lg = Large; Md = Medium; Sm = Small) and E2 status (EA = estrogen active; EI = estrogen inactive) on FGF9 mRNA in bovine granulosa cells on different days post-ovulation. abcMeans without a common letter differ (P < 0.05); n = 10, 16, 36 and 16 for Lg-EA, Lg-EI, Md-EI and Sm-EI, respectively, for day 3-4; n = 5, 17, 27 and 14 for Lg-EA, Lg-EI, Md-EI and Sm-EI, respectively, for day 5-6. Panel B: Effect of follicular size (Lg = Large; Md = Medium) and E2 status (EA = estrogen active; EI = estrogen inactive) on abundance of FGF9 mRNA in bovine theca cells on different days post- ovulation. abMeans without a common letter differ (P < 0.05); n = 9, 13 and 28 for Lg-EA, Lg-EI and Md-EI, respectively, for day 3-4; n = 4, 11 and 23 for Lg-EA, Lg-EI and Md-EI, respectively, for day 5-6. Values are normalized to constitutively expressed 18S ribosomal RNA and are least squares means ± SEM. 105 106 Fig. 2. Effects of follicular size (Lg = Large; Sm = Small) and E2 status (EA = estrogen active; EI = estrogen inactive) on concentrations of free IGF1 (Panel A), E2 and P4 (Panel B) in follicular fluid. abMeans (n = 6-18 follicles per group) without a common letter differ (P < 0.05); cdMeans (n = 6-17 follicles per group) without a common letter differ (P < 0.05). 107 108 Fig. 3. Correlation between FGF9 mRNA abundance in granulosa cells and concentrations of E2 in follicular fluid (FFL). The relationship between FGF9 mRNA abundance and concentrations of E2 in FFL collected between days 3 and 6 post-ovulation is represented by the line (—). The line is a log-fit line. 109 Fig. 4. Results from Western blotting to detect FGF9 protein in FFL. Lanes were loaded as following (from left to right): negative control (0 ng of recombinant human FGF9 in PBS); 5 ng of recombinant human FGF9 in 15 µL of PBS and 5 µL of sample buffer; 1 ng : FGF9 new trial 5 11-11-15of recombinant human FGF9 in 15 µL of PBS and 5 µL of sample buffer; 0.1 ng of 15/07/16 21:55 recombinant human FGF9 in in 15 µL of PBS and 5 µL of sample buffer; 2.5 ng of recombinant human FGF9 in 5 µL FFL, 10 µL of PBS, and 5 µL of sample buffer; 10 µL of FFL, 5 µL of PBS, and 5 µL of sample buffer; 5 µL of FFL, 10 µL of PBS, and 5 µL of MW sample buffer. Ladder Neg. Ctrl 5ng rFGF91ng PBS rFGF90.1ng PBS rFGF92.5ng PBS rFGF9smFFL smFFL smFFL 250 150 100 75 Recombinant human FGF9 50 MW 0ng 5ng 1ng 0.1ng 2.5ng 0ng 0ng 37 37 - 25 25 - 20 20 - 15 10 PBS FFL No Light:180:00m 2015-11-11 11:37AM FGF9 new trial 5 11-11-15 FGF9 Ab: 1:250 2nd Ab (G@R): 1:50,000 FluorChem E FE0622: Laboratory FCE_0622_2015-11-11_11-37-34.fcz 110 http://139.78.87.201/run_review/run_print_remote/FCE_0622_2015-11-11_11-37-34 Página 1 de 1 Fig. 5. Schematic model summarizing the hormonal regulation of FGF9 production by granulosa and theca cells. Dashed line with T at end indicates inhibitory effects; hormones by arrows with a “+” indicates stimulatory effects; hormones by arrows with a “˗” indicates inhibitory effects. IGF1, FSH and LH are stimulatory to estradiol (E2) and androstenedione (A4) production via interaction with 17-hydroxylase (CYP17A1) and aromatase (CYP19A1). Increased WNT2 and free IGF1 decreases FGF9 mRNA and this decreased FGF9 production causes a reduction in the FGF9 inhibition of E2 production by granulosa cells (GC) and A4 production by theca cells (TC), causing an overall increase in E2 production by the dominant follicle. SHH, Sonic hedgehog; T4, thyroxine; TNFa, tumor necrosis factor alpha; WNT2, wingless 2; B.M. = basement membrane. 111 CYP17A1 + LH TC IGF1 WNT2 TC TNFa GC + + FGF9 B.M. A4 ANTRUM FSH + WNT2 Free IGF1 FGF9 mRNA SHH OC + T4 + T _ _ I CYP19A1 + FSH TNFa FGF9_ T + GC IGF1 E2 FGF9 production 112 6. References Aad, P. Y., S. E. Echternkamp, and L. J. Spicer. 2013. Possible role of IGF2 receptors in regulating selection of 2 dominant follicles in cattle selected for twin ovulations and births. Domest. Anim. Endocrinol. 45: 187-195. Aad, P. Y., S. E. Echternkamp, D. D. Sypherd, N. B. Schreiber, and L. J. Spicer. 2012. 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Epidermal growth factor and basic fibroblast growth factor suppress the spontaneous onset of apoptosis in cultured rat ovarian granulosa cells and follicles by a tyrosine kinase-dependent mechanism. Mol. Endocrinol. 6: 1942-1950. Vernon, R. K., and L. J. Spicer. 1994. Effects of basic fibroblast growth factor and heparin on follicle-stimulating hormone-induced steroidogenesis by bovine granulosa cells. J. Anim. Sci. 72: 2696-2702. Voge, J. L., P. Y. Aad, C. A. T. Santiago, D. W. Goad, J. R. Malayer, D. Allen, and L. J. Spicer. 2004. Effect of insulin-like growth factors (IGF), FSH, and leptin on IGF- binding-protein mRNA expression in bovine granulosa and theca cells: quantitative detection by real-time PCR. Peptides 25: 2195-2203. 117 Woad, K. J., M. G. Hunter, G. E. Mann, M. Laird, A. J. Hammond, and R. S. Robinson. 2012. Fibroblast growth factor 2 is a key determinant of vascular sprouting during bovine luteal angiogenesis. Reproduction 143: 35-43. 118 CHAPTER IV CHANGES IN FIBROBLAST GROWTH FACTOR RECEPTORS-1c, -2c, -3c, AND -4 mRNA DURING OVARIAN FOLLICULAR GROWTH IN CATTLE 1. Abstract Fibroblast growth factors (FGFs) regulate folliculogenesis of several mammalian species, including cattle, through autocrine, paracrine, and endocrine mechanisms. The diversity of roles played by FGFs is influenced by the nature of the ligands and the diversity of high affinity fibroblast growth factors receptors (FGFRs). There are four distinct genes encoding for FGFRs (FGFR1-FGFR4) in vertebrates and the occurrence of mRNA splicing in the immunoglobulin-like domain III generates diversity of sequence and results in various isoforms of FGFR1, FGFR2, and FGFR3 genes (but not of FGFR4). Because FGFRs have different ligand-specificities, the localization of FGFRs in the different compartments of bovine antral follicles is of fundamental importance for the FGFs to exert their effects in the ovary. Hence, the objective of this study was to determine if FGFR1c, FGFR2c, FGFR3c, and FGFR4 change according to follicular size, steroidogenic status, and days post-ovulation during growth of first-wave dominant follicles in cattle exhibiting a regular estrous cycle. Estrous cycles of non-lactating dairy cattle were synchronized, and ovaries were collected on either day 3-4 (n = 8) or day 5-6 (n = 8) post-ovulation for GC and TC mRNA extraction from small (1-5 mm), medium (5.1-8 mm) or large (8.1-18 mm) follicles for real time-PCR analysis. In GC, FGFR1c and FGFR2c mRNA relative abundance was greater (P < 0.01) in estrogen (E2)-inactive (i.e., concentrations of E2 < progesterone, P4) follicles of all sizes than in GC from large E2-active follicles (i.e., concentrations of E2 < P4), FGFR3c mRNA relative abundance was greater (P < 0.05) in large and medium E2-inactive than in large E2- active follicles, and FGFR4 mRNA abundance did not differ among different groups of 119 follicles. In TC, medium E2-inactive follicles had greater (P < 0.05) FGFR1c and FGFR4 mRNA abundance than large E2-active and E2–inactive follicles at the late growing phase of the first dominant follicle whereas FGFR1c, FGFR2c, FGFR3c, and FGFR4 mRNA abundance was greater (P < 0.05) in medium E2-inactive follicles at late (day 5-6 post- ovulation) than at early (day 3-4 post-ovulation) growing phase of first dominant follicle. Taken together, the findings that FGFR1c, FGFR2c, and FGFR3c mRNA abundance was less in GC of E2-active follicles and was greater in TC of medium inactive follicles at late than at early growing phase of first dominant follicle for all FGFRs isoforms tested support an anti- differentiation role for FGFs and their FGFRs as well as support the idea that changes in FGFs and their receptors regulate selection of dominant follicles in cattle. Key Words: Fibroblast growth factor receptors (FGFRs), FGFR1c, FGFR2c, FGFR3c, FGFR4, theca cell, granulosa cell, cattle. 2. Introduction Ovarian folliculogenesis is a tightly regulated process where the somatic cells of the follicle, granulosa (GC) and theca (TC) cells, communicate in a coordinated way with the oocyte for both follicular and oocyte growth and maturation (Eppig, 1991; Elvin and Matzuk, 1998; Fortune et al., 2004). Among other growth factors that control folliculogenesis, the fibroblast growth factors (FGFs) have been emerging as important regulators of ovarian function, playing autocrine, paracrine, and endocrine roles in the regulation of development of ovarian follicles (for reviews, see Chaves et al., 2012; Price, 2016). These polypeptides belong to a family of 22 members in mammals (Ornitz and Itoh, 2001; Itoh and Ornitz, 2011), and, to date, ten members have been detected in the ovary: FGF1, 2, 7-10, 16-18, 22. In antral follicles of cattle, FGF1, FGF2, FGF7, FGF18, and FGF22 are mainly produced by TC (Parrott and Skinner, 1998; Berisha et al., 2000; Berisha et al., 2004; Buratini et al., 2007; Portela et al., 2010; Castilho et al., 2015); FGF8 is produced by GC, TC, and oocytes (Buratini et al., 2005); FGF9 is produced in greater amounts in GC than in TC (Schreiber et 120 al., 2012); FGF10 is produced by TC and oocytes (Buratini et al., 2007); FGF16 is produced by the oocyte (Ferreira et al., 2016); and FGF17 is detected mainly in oocytes, but also in GC (Machado et al., 2009). In cattle, FGFs play diverse roles in ovarian function. To date, at least four members of this polypeptide family stimulate proliferation of somatic cells of ovarian follicles: FGF1, FGF2, FGF7, and FGF9 stimulate GC and/or TC proliferation (Gospodarowicz et al., 1977a; Gospodarowicz et al., 1977b; Gospodarowicz et al., 1985; Parrott et al., 1994; Spicer and Stewart, 1996; Schreiber and Spicer, 2012; Schreiber et al., 2012). In addition, FGFs regulate steroidogenesis: FGF2, FGF7, and FGF18 inhibit FSH-stimulated estradiol (E2) and LH- stimulated progesterone (P4) production by GC (Vernon and Spicer, 1994; Spicer and Stewart, 1996; Wandji et al., 1996; Parrott and Skinner, 1998; Machado et al., 2009; Portela et al., 2010); FGF9 attenuates insulin-like growth factor 1-stimulated E2 and P4 production by GC (Schreiber and Spicer, 2012) and suppresses insulin-like growth factor 1-stimulated P4 production by TC (Schreiber et al., 2012). In order to exert their actions in the ovary, FGFs need to bind to high affinity receptors (FGFRs). The FGFR is a single chain transmembrane tyrosine kinase with two or three immunoglobulin-like domains and a heparin-binding domain in the extracellular ligand- binding portion (Plotnikov et al., 2000; Ornitz and Itoh, 2001; Itoh and Ornitz, 2004; Li et al., 2016). There are four distinct genes encoding for FGFRs (FGFR1-FGFR4) in vertebrates and mRNA alternative splicing occurs in the immunoglobulin-like domain III of the FGFR1, FGFR2, and FGFR3 genes (but not of FGFR4), generating diversity of sequence and resulting in various isoforms (Itoh and Ornitz, 2004; Ornitz and Itoh, 2015; Li et al., 2016). The ligands of the FGF family have different affinities for these receptors (Itoh and Ornitz, 2004), which are determined by the immunoglobulin-like domains (Dell and Williams, 1992). According to ligand binding specificity, the preferred receptors for FGFs produced in the ovary are: FGFR1c for FGF1 and FGF2; FGFR2b for FGF7, FGF10, and FGF22; FGFR3c for FGF1, FGF2, FGF8, FGF9, FGF16, FGF17, and FGF18 (Ornitz and Itoh, 2015). In 121 addition, FGFR1b is the second preferred for FGF7, FGF10, and FGF22; FGFR2c is the second preferred for FGF9 and FGF16; and FGFR4 is the second preferred for FGF8, FGF17, and FGF18 (Ornitz and Itoh, 2015). Since FGFRs have different ligand-specificities, the localization of FGFRs in the different compartments of bovine antral follicles is of fundamental importance for the FGFs effects: FGFR1b has been detected in GC, TC, and oocytes (Zhang and Ealy, 2012; Castilho et al., 2015); FGFR1c and FGFR2b have been detected in GC and oocytes (Berisha et al., 2004; Buratini et al., 2007; Machado et al., 2009; Zhang and Ealy, 2012); FGFR2c and FGFR3c have been detected in both GC and TC (Berisha et al., 2004; Buratini et al., 2005); FGFR4 has been detected exclusively in TC (Buratini et al., 2005). In addition, some FGFRs change according to follicular fate in cattle: FGFR1b and FGFR2b GC mRNA abundance is greater in future subordinate follicles than in future dominant follicles (Berisha et al., 2004; Castilho et al., 2015); FGFR3c mRNA abundance is greater in GC (but not in TC) of small healthy follicles and in response to FSH (Buratini et al. 2005); FGFR4 mRNA abundance is greater in small than in large follicles (Buratini et al., 2005). Nevertheless, information of how endogenous production of FGFRs by ovarian follicular cells change during selection of dominant follicles in cattle needs further clarification. Hence, the objective of this study was to determine if mRNA abundance of FGFR1c, FGFR2c, FGFR3c, and FGFR4 in GC and TC changes during growth of first-wave dominant follicles in cattle exhibiting regular estrous cycle. 3. Material and Methods Animals and Experimental Design Non-lactating Holstein cows (n = 16), culled for non-reproductive reasons from Oklahoma State University herd, were used for this experiment as previously described (Dentis et al., 2016). Briefly, estrous cycles were synchronized using two injections (i.m.) of ® prostaglandin F2α (Lutalyse , 25 mg) with an interval of 11 days, after which, follicle 122 development was monitored daily via ultrasonography using an Aloka 500V with a 7.5 MHz probe. Following ovulation, cows were assigned to be ovariectomized either at day 3-4 (early growing phase of the first dominant follicle; n = 8 cows) or day 5-6 post-ovulation (late growing phase of the first dominant follicle; n = 8 cows). After each ovariectomy, ovaries were put on ice, and transported to the laboratory where diameters of all follicles ≥ 5 mm (surface diameter) in diameter were recorded, and ovarian tissue and fluid collected (Dentis et al., 2016). The animal experimentation described in this report was approved by the Oklahoma State University Institutional Animal Care and Use Committee (Protocol No. AG106). Cell and Follicular Fluid Collection For GC sample collection, follicles were categorized by surface diameter as small (1- 5 mm), medium (5.1-8 mm) or large (8.1-18 mm); TC samples were collected from only medium and large follicles. Follicular fluid (FFL) from medium and large follicles was aspirated individually and centrifuged to obtain GC, and FFL from small follicles was pooled within each ovary and then centrifuged to obtain GC as previously described (Stewart et al., 1996; Dentis et al., 2016). After centrifugation, FFL was aspirated and stored at -20 °C for measurement of E2 and P4 via RIA. After collection of FFL, each medium and large follicle was bisected in situ, the inner wall was scraped, rinsed with Ham’s F-12 to remove any remaining GC, and these GC were combined with GC collected from FFL as previously described (Schreiber and Spicer, 2012; Dentis et al., 2016). GC collected from small follicles were kept separate for each ovary. GC were lysed in 0.5 mL of TRIzol® reagent solution (Life Technologies, Inc., Grand Island, NY) and stored frozen at -80 °C until RNA extraction (see description below). TC were dissected from the bisected follicles and placed in 0.75 mL of TRIzol Reagent and homogenized for 2-3 min on ice using the Omni TH tissue homogenizer (Omni International Inc., Marietta, GA) with Omni Tip™ disposable generator probes as previously described (Aad et al., 2012). RNA Extraction and Quantitative PCR (qPCR) 123 Ovarian GC and TC mRNA was isolated as described elsewhere (Voge et al., 2004). RNA samples were solubilized in diethylpyrocarbonate-treated water (Life Technologies), quantitated at 260 nm using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies Inc., Wilmington, DE), and stored at -80 °C. Primers and probes for FGFR1c, FGFR2c, FGFR3c, and FGFR4 (supplied as 5’ FAM reporter dye and a 3’ TAMRA quencher dye; TaqMan TAMARA; Applied Biosystems Inc., Foster City, CA) for quantitative qPCR (Table 1) were designed using Primer Express software (Foster City, CA) as previously reported (Grado-Ahuir et al., 2011). A “highly similar sequences” BLAST query search (http://blast.ncbi.nlm.nih.gov/Blast.cgi) was conducted for each primer and probe to ensure specificity of the designed primers and probes. Relative mRNA abundance of target genes was quantified using fluorescent quantitative single-step RT-PCR using a CFX96TM Real-Time PCR Detection System (Bio-Rad Laboratories, Inc., Hercules, CA). Target gene expression was normalized to constitutively expressed 18S ribosomal RNA (18S rRNA; supplied as a VIC probe; TaqMan Ribosomal RNA Control Reagent, Applied Biosystems Inc.) and relative quantity of target gene mRNAs was expressed as 2-ΔΔCt using the relative comparative threshold cycle (Ct) method as previously described (Livak and Schmittgen, 2001; Voge et al., 2004; Lagaly et al., 2008). Radioimmunoassays (RIA) Concentrations of P4 and E2 in FFL were determined by RIA as previously described (Stewart et al., 1996; Dentis et al., 2016). All samples were run in one assay for each of the steroid RIA. The intra-assay coefficient of variation for P4 and E2 RIA was 11.6 % and 10.6 %, respectively. Statistical Analyses Through analysis of these data, we sought to determine if FGFR1c, FGFR2c, FGFR3c, and FGFR4 mRNA abundance varies in GC and TC at different periods of follicular development and according to follicular size and estrogenic status. Data were 124 analyzed via factorial ANOVA with GLM procedures of SAS for Windows (version 9.2, SAS Institute Inc., Cary, NC) and are presented as the least squares means (± SEM) of measurements. Main factors were days post-ovulation (early, day 3-4, and late, day 5-6, growing phase of the first dominant follicle), and follicle status based on size (small, medium, or large in the case of GC, and medium or large in the case of TC) and estrogenic status (E2 active: E2>P4 concentrations in FFL or E2 inactive: E2 4. Results Follicle size, E2, and P4 Concentrations in follicular fluid Follicle size and steroid concentrations in FFL have been reported for this study (Dentis et al., 2016). Briefly, diameter of large dominant E2-active, large subordinate E2- inactive, and medium E2-inactive follicles averaged 12.9 ± 0.5, 9.48 ± 0.36, and 6.37 ± 0.23 mm, respectively. Concentrations of E2 in FFL of large dominant E2-active, large subordinate E2-inactive, medium E2-inactive, and small E2-inactive follicles averaged 186.5 ± 29.5, 8.45 ± 3.7, 2.3 ± 0.8, and 2.0 ± 0.2 ng/ml, respectively. Concentrations of P4 in FFL did not differ (P > 0.10) among follicle groups and ranged between 61 ± 7 and 236 ± 42 ng/ml. 125 GC FGFR1c mRNA Relative Abundance Abundance of FGFR1c mRNA, the main receptor for FGF1 and FGF2, was significantly affected by follicle group, but not by days post-ovulation or their interaction. Specifically, FGFR1c mRNA abundance was greater (P < 0.01) in large, medium, and small E2-inactive (E2/P4 ratio < 1) than in large E2-active (E2/P4 ratio > 1) follicles (4.3-, 6.1-, and 4.2-fold, respectively) and was 1.4–fold greater (P < 0.05) in medium E2-inactive than in large and small E2-inactive follicles (Fig. 1A). No other significant differences were detected among follicles of different sizes and steroidogenic status. GC FGFR2c mRNA Relative Abundance Abundance of FGFR2c mRNA, the second main receptor for FGF9 and FGF16, was significantly affected by follicle group, but not by days post-ovulation or their interaction (Fig. 1B). Specifically, FGFR2c mRNA abundance was greater (P < 0.01) in large, medium, and small E2-inactive than in large E2-active follicles (7.5-, 10.4-, and 4.9-fold, respectively). No other significant differences were detected among follicles of different sizes and steroidogenic status. GC FGFR3c mRNA Relative Abundance Abundance of FGFR3c mRNA, the main receptor for FGF8, FGF9, FGF16, FGF17, and FGF18, was significantly affected by follicle group, but not by days post-ovulation or their interaction (Fig. 1C). Specifically, FGFR3c mRNA abundance was greater (P < 0.05) in large and medium E2-inactive than in large E2-active follicles (3.3- and 3.7-fold, respectively) and tended to be greater (P = 0.06) in small E2-inactive than in large E2-active follicles (Fig. 1C). No other significant differences were detected among follicles of different sizes and steroidogenic status. GC FGFR4 mRNA Relative Abundance 126 Abundance of FGFR4 mRNA was not different (P > 0.10) among follicles of different sizes and steroidogenic status or days post-ovulation (Fig. 1D). TC FGFR1c mRNA Relative Abundance Abundance of FGFR1c mRNA in TC was affected (P < 0.05) by follicle group, days post-ovulation, and their interaction. Specifically, FGFR1c mRNA abundance was (2.7- and 1.7-fold, respectively) greater (P < 0.05) in medium E2-inactive than in large E2-active and small E2–inactive follicles at late growing phase of first dominant follicle (Fig. 2A). Moreover, FGFR1c mRNA abundance was 2–fold greater in medium E2-inactive at late than at early growing phase of first dominant follicle. No significant differences in FGFR1c mRNA abundance were detected between large E2-active, large E2-inactive and medium E2- inactive follicles at early growing phase of first dominant follicle. TC FGFR2c mRNA Relative Abundance Abundance of FGFR2c mRNA tended (P < 0.07) to be affected by follicle group x days post-ovulation such that FGFR2c mRNA abundance was 1.9–fold greater (P < 0.05) in medium E2-inactive follicles at late than at early growing phase of first dominant follicle (Fig. 2B). No other significant differences were detected among follicles of different sizes and estrogen activity at early or late growing phases of first dominant follicle. TC FGFR3c mRNA Relative Abundance Abundance of FGFR3c mRNA tended (P < 0.10) to be affected by the follicle group by days post-ovulation interaction such that FGFR3c mRNA abundance was 2.7–fold greater (P < 0.05) in medium E2-inactive than in large E2-inactive follicles at late growing phase of first dominant follicle (Fig. 2C). In addition, FGFR3c mRNA abundance was 1.8–fold greater (P < 0.01) in medium E2-inactive follicles at late days post-ovulation than at early days post- ovulation. No other significant differences were detected between follicles of different sizes at early or late growing phases of first dominant follicle. 127 TC FGFR4 mRNA Relative Abundance Abundance of FGFR4 tended (P < 0.09) to be affected by the follicle group by days post-ovulation interaction such that FGFR4 mRNA abundance was 1.4–fold greater (P < 0.05) in medium E2-inactive at late days post-ovulation than at early days post-ovulation (Fig. 2D). In addition, FGFR4 mRNA abundance was (5.2- and 1.7-fold, respectively) greater (P < 0.05) in medium E2-inactive than in large E2-active and E2–inactive follicles at late growing phase of first dominant follicle. No other significant differences were detected between follicles of different sizes at early or late growing phases of first dominant follicle. Correlations among Follicular Size, FFL Levels of Steroids, and FGFRs mRNA Relative Abundance In GC, negative correlations existed between follicular size and FGFR1c (r = -0.30, P < 0.01, n = 141) and FGFR2c mRNA abundance (r = - 0.23, P < 0.01, n = 142). In TC, a negative correlation existed between follicular size and FGFR4 (r = -0.23, P < 0.05, n = 82). No significant correlations were observed between follicular size and FGFR3c or FGFR4 mRNA abundance in GC or between follicular size and FGFR1c, FGFR2c, or FGFR3c mRNA abundance in TC. In GC, correlations between FFL concentrations of E2 and FGFRs mRNA abundance were negative for all FGFR isoforms. Specifically, a negative correlation existed between FFL E2 concentrations and FGFR1c (r = -0.20, P < 0.05, n = 136) and FGFR2c (r = -0.17, P < 0.01, n = 137) mRNA abundance. Also, log-transformed values of FGFR3c (r = -0.24, P < 0.05, n = 135) and FGFR4 (r = -0.22, P < 0.05, n = 138) mRNA abundance were negatively correlated to levels of E2 and log-transformed values of levels of E2 in FFL, respectively. In TC, a negative correlation existed between FFL E2 concentrations and FGFR1c (r = -0.25, P < 0.05, n = 79) and between log-transformed values of FGFR4 (r = -0.30, P < 0.05, n = 78) mRNA abundance and FFL E2 concentrations whereas no significant correlations were observed between FFL concentrations of E2 and FGFR2c or FGFR3c mRNA abundance. 128 In GC, positive correlations were detected between FFL concentrations of P4 and log-transformed FGFR1c (r = 0.27, P < 0.01, n = 127), FGFR2c (r = 0.21, P < 0.05, n = 129), and log-transformed FGFR3c (r = 0.26, P < 0.01, n = 127) mRNA relative abundance. In TC, log-transformed values of levels of P4 in FFL were correlated with log-transformed values of FGFR1c (r = 0.35, P < 0.05, n = 74) and FGFR4 (r = 0.24, P < 0.05, n = 73) mRNA relative abundance. No significant correlations were detected between FFL concentrations of P4 and GC FGFR4 mRNA abundance or TC FGFR2c and FGFR3c mRNA abundance. In GC, negative correlations were detected between FGFR1c (r = - 0.22, P < 0.05, n = 125), log-transformed FGFR2c (r = - 0.54, P < 0.01, n = 127), or log-transformed FGFR3c (r = - 0.29, P < 0.01, n = 125) mRNA relative abundance and E2/P4 concentrations ratio in FFL. In TC, log-transformed value of FGFR1c mRNA abundance was negatively correlated with E2/P4 concentrations ratio in FFL (r = -0.30, P < 0.01, n = 73). No significant correlations were detected between FFL E2/P4 concentrations ratio and GC FGFR4 mRNA abundance and between FFL E2/P4 concentrations ratio and TC FGFR2c, FGFR3c, or FGFR4 mRNA abundance. 5. Discussion Actions of FGFs on the ovary were first reported in the seventies (Gospodarowicz et al., 1977a; Gospodarowicz et al., 1977b), when FGF1 was found to stimulate proliferation of bovine granulosa and luteal cells. To date, ten members of the FGF family have been shown to regulate ovarian folliculogenesis, binding to FGFRs to elicit GC and TC proliferation and steroidogenesis (for reviews, see Chaves et al., 2012; Li, 2016). The diversity of roles played by FGFs is influenced by the nature of the ligands and the diversity of high affinity FGFRs and cofactors that regulate the FGF signaling complex (Givol and Yayon, 1992; Itoh and Ornitz, 2004; Dailey et al., 2005; Li et al., 2016). In the present study, FGFR1c and FGFR2c mRNA abundance was greater in GC from E2-inactive follicles of all sizes than in GC from large E2-active follicles whereas FGFR3c mRNA abundance was greater in GC from large 129 and medium E2-inactive, and tended to be greater in GC from small E2-inactive than in large E2-active follicles. In addition, TC from medium E2-inactive follicles had greater FGFR1c mRNA abundance than TC from large E2-active follicles while FGFR1c, FGFR2c, and FGFR3c mRNA abundance was greater in TC from medium E2-inactive follicles at late than at early growing phase of first dominant follicle. Furthermore, abundance FGFR1c, FGFR2c, and FGFR3c mRNA in GC was negatively correlated with FFL E2 concentrations and E2/P4 ratio and positively correlated with P4 concentrations whereas FGFR1c mRNA abundance in TC was also negatively correlated with FFL E2 concentrations and E2/P4 ratio and positively correlated with FFL P4 concentrations. Because a follicle’s estrogenic status can be used to assess the health of follicles, large E2-active follicles are considered as those selected to escape atresia and become dominant (Ireland and Roche, 1982; Spicer and Echternkamp, 1986), and the present results indicate that FGFR1c, FGFR2c, and FGFR3c are produced in greater amounts in GC and TC from subordinate than from dominant follicles, implying a pro-atretic or an anti-differentiation role for these receptors. The fact that relative abundance of mRNA for FGFR1c and FGFR2c in GC is negatively correlated with size and E2/P4 ratio reinforces this idea. Relative abundance of GC FGFR4 mRNA was not different among follicles of different estrogenic status and sizes, but it was greater in TC from medium E2-inactive follicles at days 5 to 6 post-ovulation than at days 3 to 4 post-ovulation. In addition, FGFR4 mRNA abundance in TC was negatively correlated with size and with FFL E2 concentrations and positively correlated with FFL P4 concentrations. Since transcripts for FGFR4 only changed in TC, but not in GC, of different groups of follicles across days, it is likely to suppose that the action of the ligands that bind to FGFR4 may be more regulated in TC than in GC. This is in agreement to previous observations (Buratini et al., 2005a) where FGFR4 mRNA was only detected in TC, but not in GC or oocytes, from bovine antral follicles. Moreover, the fact that FGFR4 mRNA is increasing in E2-inactive follicles as the time of follicular dominance approaches is an indication that this receptor would be playing a role in 130 preventing differentiation of bovine antral follicles. This is also in agreement with previous findings (Buratini et al., 2005a), where transcripts for FGFR4 were greater in TC from small than from large antral follicles of cattle. Interestingly, many ligands that preferentially bind to FGFR1c, FGFR2c, FGFR3c, and FGFR4 appear to be critical regulators of large follicle differentiation and atresia. For example, FGF2 (preferentially binding to FGFR1c and FGFR3c), FGF9 (preferentially binding to FGFR3c followed by FGFR2c), and FGF17 and FGF18 (preferentially binding to FGFR3c followed by FGFR4) inhibit steroidogenic enzyme activity and FSH-stimulated E2 production by GC in cattle (Vernon and Spicer, 1994; Machado et al., 2009; Portela et al., 2010; Schreiber and Spicer, 2012). Because E2 is important for GC survival and differentiation of dominant follicles (Knecht et al., 1985; Fortune et al., 2004), FGFs suppressing E2 production may be playing a role in inducing atresia or preventing differentiation of GC in cattle. The fact that some of the ligands that preferentially bind to FGFR3c, including FGF9, FGF17, and FGF18, have a greater mRNA abundance in subordinate or atretic antral follicles than in dominant follicles in cattle (Machado et al., 2009; Portela et al., 2010; Schreiber et al., 2012) reinforces this idea. Furthermore, of the ligands mentioned above, FGF18 induced regression of the dominant follicle when injected in vivo and increased cleaved caspase-3 in GC in vitro (Portela et al., 2015), which is a major downstream effector of apoptosis and serves a marker for GC apoptosis (Feranil et al., 2005), confirming the role for this polypeptide in induction of atresia in bovine antral follicles. It is noteworthy that some members of the FGF family that preferentially bind to FGFR1c and/or FGFR3c are mitogenic factors of ovarian follicle somatic cells of cattle. Specifically, FGF1 (Gospodarowicz et al., 1977a) stimulate GC proliferation whereas FGF2 (Gospodarowicz et al., 1985; Spicer and Stewart, 1996), and FGF9 (Schreiber and Spicer, 2012; Schreiber et al., 2012) stimulate both GC and TC proliferation. In addition, FGF8 appears to be stimulating GC proliferation, since it leads to expression of genes related to cell proliferation, such as MAPK3/1 and MAPK14, in GC (Jiang et al., 2013; Price, 2016). Hence, 131 FGFR1c and FGFR3c appear to be playing a positive role in early development of bovine antral follicles. In summary, FGFR1c, FGFR2c, FGFR3c had greater mRNA abundance in GC of medium, large, and/or small E2-inactive follicles than in large E2-active follicles and FGFR1c, FGFR2c, FGFR3c, FGFR4 mRNA abundance was greater in TC of medium E2- inactive follicles at late than at early growing phase of first dominant follicle. Furthermore, FGFR1c and FGFR4 mRNA relative abundance was greater in TC of medium E2-inactive follicles than large E2-active and E2-inactive follicles at late than at early growing phase of first dominant follicle. Taken together with the fact that several of their ligands are produced in greater amounts by subordinate than by dominant follicles and inhibit E2 production, the present findings suggest a role for FGFs and their FGFRs as anti-differentiation factors of follicular somatic cells, avoiding the selection of multiple follicles to become dominant in a mono-ovulatory species such as cattle. Acknowledgments The authors thank Jeff Williams for his laboratory assistance; David Jones, Jeff Davis and other members of the OSU Dairy Cattle Center for care and management of the cows. This work supported in part by: the NICHD, National Institutes of Health, through Agreement R15-HD-066302, and the Oklahoma State University Agricultural Experiment Station. 132 Table 1. Information about primers and probes. Gene Oligo Sequence Accession Tm (°C) FGFR1c FWD AGGTGAACGGGAGTAAGATTGG XM_010820329.2 56.5 REV GTGCAGCACCTCCATCTCTTT 57.6 Probe TCTTGAAGACGGCCGCCGGAGTTAACA 63.3 CCA FGFR2c FWD GTTCCAATGCGGAAGTGCTG XM_010820096.2 57.1 REV GTTTTGGCAGGACAGTGAGC 56.8 Probe AGGCGGATGCTGGCGAGTATATTTGTA 63.9 AGG FGFR3c FWD TAACACCACCGACAAGGAGC XM_014478386.1 57.2 REV CCACGCAGAGTGATGGGAAA 57.6 Probe TGCGCAATGTCACCTTTGAGGACG 62.0 FGFR4 FWD CACTGCCCCCCAGAGCTATAC XM_005209123.2 59.5 REV AGGACCTTGTCCAGTGCCTCTA 59.6 Probe AGCACCCTCTCAGAGGCCCACTTTCA 65.3 133 Fig. 1. Effects of follicular size (Lg = Large; Md = Medium; Sm = Small) and E2 status (EA = estrogen active; EI = estrogen inactive) on FGFR1c, FGFR2c, FGFR3c, and FGFR4 mRNA relative abundance in bovine granulosa cells. Panel A: Effects of follicular size and E2 status on FGF1c mRNA in bovine granulosa cells (GC); n = 16, 33, 64, and 29 and for Lg-EA, Lg-EI, Md-EI and Sm-EI, respectively. Panel B: Effects of follicular size and E2 status on FGF2c mRNA in bovine GC; n = 16, 33, 62, and 28 for Lg-EA, Lg-EI, Md-EI and Sm-EI, respectively. Panel C: Effects of follicular size and E2 status on FGF3c mRNA in bovine GC; n = 16, 32, 61, and 28 for Lg-EA, Lg-EI, Md-EI and Sm-EI, respectively. Panel D: Effects of follicular size and E2 status on FGF4 mRNA in bovine GC; n = 15, 28, 61, and 29 for Lg-EA, Lg-EI, Md-EI and Sm-EI, respectively. Values are normalized to constitutively expressed 18S ribosomal RNA and are least squares means ± pooled SEM of values averaged across day 3 to 4 and day 5 to 6 post-ovulation. abcWithin a panel, means without a common letter differ (P < 0.05). 134 (A) FGFR1c in GC (B) FGFR2c in GC mRNA relative abundance relative mRNA (C) FGFR3c in GC (D) FGFR4 in GC mRNA relative abundance relative mRNA 135 Fig. 2. Effects of follicular size (Lg = Large; Md = Medium; Sm = Small) and E2 status (EA = estrogen active; EI = estrogen inactive) on FGFR1c, FGFR2c, FGFR3c, and FGFR4 mRNA abundance in bovine theca cells (TC) on different days post-ovulation. Panel A: Effects of follicular size and E2 status on FGF1c mRNA in bovine TC; n = 9, 10, and 27 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 3-4; n = 4, 11, and 22 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 5-6. Panel B: Effects of follicular size and E2 status on FGFR2c mRNA in bovine TC; n = 9, 12, and 23 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 3-4; n = 4, 10, and 20 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 5-6. Panel C: Effects of follicular size and E2 status on FGFR3c mRNA in bovine TC; n = 8, 12, and 26 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 3-4; n = 4, 11, and 22 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 5-6. Panel D: Effects of follicular size and E2 status on FGFR4 mRNA in bovine TC; n = 9, 11, and 25 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 3-4; n = 4, 11, and 22 for Lg-EA, Lg-EI, and Md-EI, respectively, for day 5-6. Values are normalized to constitutively expressed 18S ribosomal RNA and are least squares means ± pooled SEM. abWithin a panel, means without a common letter differ (P < 0.05). 136 (A) FGFR1c in TC (B) FGFR2c in TC mRNA relative abundance relative mRNA (C) FGFR3c in TC (D) FGFR4 in TC relative abundance relative mRNA 137 6. References Aad, P. Y., S. E. Echternkamp, D. D. Sypherd, N. B. Schreiber, and L. J. Spicer. 2012. The hedgehog system in ovarian follicles of cattle selected for twin ovulations and births: Evidence of a link between the IGF and hedgehog systems. Biol. Reprod. 87: 1-10. Berisha, B., D. Schams, M. Kosmann, W. Amselgruber, and R. Einspanier. 2000. 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Endocrinol. 42: 230-238. 143 CHAPTER V TRANSCRIPTOME PROFILING OF BOVINE THECA CELLS TREATED WITH FIBROBLAST GROWTH FACTOR 9 1. Abstract Fibroblast growth factor 9 (FGF9), a member of a large family of single chain polypeptide factors, controls several functions in many different tissues of mammals. In the ovaries of cattle, FGF9 appears to be acting as an anti-differentiation factor, stimulating in vitro proliferation of granulosa (GC) and theca (TC) cells while suppressing steroidogenesis of these cells in the presence of insulin-like growth factor 1 (IGF-1). Also, FGF9 mRNA abundance in GC and TC changes according to the size and estrogenic status of follicles and days post-ovulation in cattle. Nevertheless, information about signaling mechanisms activated by FGF9 in TC is somewhat lacking. Therefore, the objective of this study was to investigate how bovine TC from large ovarian follicles respond to exogenous FGF9 in vitro. In order to detect differentially expressed transcripts by TC following FGF9 in vitro treatment, microarray technology was utilized. Ovaries were obtained from beef heifers at a local abattoir, TC were isolated from large antral follicles (8.1-22 mm in surface diameter), and cultured in basal medium containing 10% FCS for 48 h prior to treatment with or without 30 ng/mL of FGF9 for 24 h in the presence of LH and IGF-1. Following treatment, total RNA was extracted from TC and processed for microarray. A total of eight chips (Affymetrix GeneChip Bovine Genome Arrays) were hybridized with RNA extracted from four biological replicates of the same number of TC pools in a paired design for the two treatments (FGF9 or control). Affymetrix GeneChip Operating Software was used to quantitate each GeneChip® and summary intensities for each probe were loaded into DNA-Chip Analyzer (dChip) for analysis. Paired t-tests were calculated using dChip to evaluate significant differences 144 between treatments. Analysis of hybridized GeneChip Bovine Genome arrays comparing FGF9-treated TC with control TC identified 355 differentially expressed transcripts, with 164 elements up-regulated and 191 elements down-regulated by FGF9. The QIAGEN’s Ingenuity® Pathway Analysis was utilized to investigate how FGF9 treatment affects molecular pathways, biological functions, and the connection between molecules in bovine TC. The IPA software identified differentially expressed transcripts in 346 pathways in response to FGF9 in TC involved in functions such as cell cycle, growth, development, proliferation, death and survival, cellular assembly and organization, and steroidogenesis. Networks of differentially expressed transcripts unveiled interesting relationships among genes related to cellular growth and proliferation and to steroidogenesis. Overall, genes, pathways, and networks identified in this study painted an interesting picture of how FGF9 regulates folliculogenesis, providing novel candidates for further investigation of FGF9 functions in the ovary of cattle. Keywords: cattle; cell proliferation; Fibroblast growth factor-9 (FGF9); microarray; steroidogenesis; theca cell. 2. Introduction Fibroblast growth factors (FGFs) constitute a large family of single chain polypeptide factors present in both vertebrates and invertebrates (Ornitz and Itoh, 2001; Itoh and Ornitz, 2011; Li et al., 2016). Currently, 22 different members have been reported in mammals (FGF1 to 23), binding to high affinity receptors and several cofactors to play a variety of roles in various tissues (Givol and Yayon, 1992; Itoh and Ornitz, 2004; Dailey e al., 2005). Fibroblast growth factor 9 (FGF9) was originally isolated from human glioma cells and characterized as a mitogenic factor (Miyamoto et al., 1993). In the last two decades, research has shown that this polypeptide plays diverse roles in many different tissues, including heart (Lavine et al., 2005; Singla et al., 2015), cartilage (Weksler et al., 1999), liver (Antoine et al., 2007), intestine (Geske et al., 2008), and reproductive (Colvin et al., 2001; 145 Drummond et al., 2007) and nervous systems (Reuss et al., 2000; Meier et al., 2014). In these tissues, FGF9 binds to FGF receptors (FGFR1c, FGFR2c, FGFR3c, FGFR3b, and FGFR4) to activate specific tyrosine residues and downstream intracellular signaling pathways, including the RAS-MAPK, PI3K-AKT, PLCγ, and STAT pathways, which regulate cell proliferation, survival, metabolism, and differentiation (Ornitz and Itoh, 2015). In fact, FGF9 has been shown to regulate sex determination (Kim et al., 2006), steroidogenesis (Schreiber and Spicer, 2012; Schreiber et al., 2012; Lai et al., 2014), tissue development (Harada et al., 2009), wound healing (Zheng et al., 2014), and even mood disorders (Aurbach et al., 2015). Moreover, expression of FGF9 has been related to brain (Todo et al., 1998) and gastric (Sun et al., 2015) cancers. In the ovaries, FGF9 was first described to be present in murine corpora lutea, stromal, and theca cells (TC) and was observed to stimulate progesterone (P4) production by granulosa cells (GC) in a paracrine way (Drummond et al., 2007). In porcine GC, FGF9 in the presence of insulin-like growth factor 1 (IGF-1) stimulated cell proliferation and steroidogenesis (Evans et al., 2014). In cattle, FGF9 has been suggested to be an anti- differentiation factor by stimulating in vitro proliferation of TC and GC while suppressing P4 production by TC and GC and estradiol (E2) production by GC in the presence of IGF-1 (Schreiber and Spicer, 2012; Schreiber et al., 2012). Abundance of FGF9 mRNA in GC and TC is hormonally regulated (Schreiber and Spicer, 2012; Schreiber et al., 2012) and changes according to the size and estrogenic status of follicles and days post-ovulation in cattle (Schütz et al., 2016, unpublished data). Hence, it seems clear that FGF9 is an important regulator of ovarian function in mammals, but its role may differ between monotocous and polytocous animals. Nevertheless, detailed information about signaling mechanisms activated by FGF9 in TC is lacking. The technology of microarray is a powerful tool for one to investigate how a specific cell type reacts to certain stimuli, enabling the simultaneous measurement of thousands of gene transcripts (Schena et al., 1995). Therefore, we utilized this resource to investigate how 146 bovine TC from large ovarian follicles respond to exogenous FGF9 in vitro. Unveiling signaling pathways activated by FGF9 in TC may provide valuable information to understand molecular aspects of cell proliferation, steroidogenesis, and apoptosis in a mono-ovulatory species such as cattle. 3. Material and Methods Reagents and Hormones The reagents used in cell culture were Ham’s F-12 (F12), DMEM, gentamicin, glutamine, sodium bicarbonate, trypan blue, deoxyribonuclease (DNase), and collagenase from Sigma-Aldrich Chemical Co. (St. Louis, MO), and fetal calf serum (FCS) from Equitech-Bio, Inc. (Kerrville, TX). The hormones used in cell culture were recombinant human FGF9 and IGF-1 (R&D Systems, Minneapolis, MN; all carrier-free), and ovine LH (NIDDK-oLH-26; activity: 1.0× NIH-LH-S1 U/mg) from the National Hormone & Pituitary Program (Torrance, CA). Cell Collection and In Vitro Culture Ovaries were obtained from beef heifers at a local abattoir and transported to the laboratory in 0.9% saline with 1% streptomycin/penicillin on ice. TC were isolated from large antral follicles (8.1-22 mm in surface diameter) with adequate vascularity and moderately transparent follicular fluid as previously described (Stewart et al., 1995; Lagaly et al., 2008). Briefly, follicles were bisected, GC were scraped free from the theca interna and the theca interna tissue was removed via microdissection and enzymatically digested for 1 h at 37 °C on a rocking platform. Non-digested thecal tissue was removed via filtration through a 149 µm mesh screen (Gelman Sciences, Ann Arbor, MI, USA). TC were then centrifuged at 50 x g for 7 min, washed twice in medium (1:1 DMEM and F12 containing 2.0 mM glutamine, 0.12 mM gentamicin, and 38.5 mM sodium bicarbonate), and resuspended in serum-free medium containing collagenase and DNase at 1.25 and 0.5 mg/mL, respectively, to prevent clumping of cells before plating (Lagaly et al., 2008). 147 Viability of TC was determined by trypan blue exclusion test and viable cells were transferred to Falcon 24-well multiwell plates (Becton Dickinson, Lincoln Park, NJ, USA) with medium containing 10% FCS. Cells were cultured at 38.5 °C in a humidified 95% air and 5% CO2 environment for the first 48 h with a medium change at 24 h. Following, TC were washed twice in serum-free medium and cultured in 1 mL serum-free medium containing 15 ng/mL of LH and 15 ng/mL of IGF-1 with or without 30 ng/mL of FGF9 for 24 h. RNA Extraction, Microarray and Statistical Analyses Following treatment, TC were lysed with 0.5 mL of TRIzol® Reagent (Life Technologies Inc., Gaithersburg, MD) and total RNA was extracted as previously described (Lagaly et al., 2008; Grado-Ahuir et al., 2009). Affymetrix GeneChip Bovine Genome Arrays (Affymetrix, Santa Clara, CA) were used for the microarray as previously described (Grado- Ahuir et al., 2011). This particular array is designed to monitor expression of approximately 23,000 bovine transcripts through 24,072 probe sets. A total of eight chips were hybridized with RNA extracted from four biological replicates of the same number of TC pools in a paired design for the two treatments (FGF9 or control). Each pool of TC was generated from 5 to 7 large follicles. The processing of RNA, including RNA purification and hybridization of microarray slides, was performed by the University of Tulsa Microarray Core Facility. Affymetrix GeneChip Operating Software (GCOS ver. 1.1.1, Affymetrix, Santa Clara, CA) was used to quantitate each GeneChip®. Summary intensities for each probe were loaded into DNA-Chip Analyzer (dChip), version 1.3, for normalization, standardization, and analysis. Paired t-tests were calculated using dChip to evaluate significant differences between treatments as previously described (Grado-Ahuir et al., 2009; Grado-Ahuir et al., 2011). Microarray Functional Data Analysis To explore the biological knowledge associated with the statistically significant probe sets from the microarray chips in addition to the annotation produced along with statistical 148 comparisons in dChip, the QIAGEN’s Ingenuity® Pathway Analysis (IPA®; QIAGEN Redwood City, http://www.qiagen.com/ingenuity) was utilized. The analyses were performed to investigate how FGF9 treatment affects molecular pathways, biological functions, and the connection between molecules in bovine TC. 4. Results Analysis of hybridized GeneChip Bovine Genome arrays comparing FGF9-treated TC with control identified 355 differentially expressed transcripts (p < 0.05 according to t- tests and at least 1.3-fold change), with 164 elements up-regulated and 191 elements down- regulated. The IPA software utilized a total of 345 differentially expressed transcripts in its analysis. The 20 genes found to be the most up- and down-regulated among the differentially expressed genes are summarized in Table 1 and Table 2, respectively, in order of fold-change. Identification of Molecular Canonical Pathways Altered by FGF9 Treatment The IPA software identified differentially expressed transcripts in 346 pathways in response to FGF9 in TC. The top ten canonical pathways affected by FGF9 (based on p-value on negative log scale) are shown in Fig. 1. The main functions associated with the top altered pathways include cellular assembly and organization, and cell cycle, growth, development, proliferation, death and survival. In addition to these, it is noteworthy to mention that FGF9 treatment affected transcripts for genes in pathways related to ovarian steroidogenesis, including: Wnt/β-catenin signaling, IGF-1 signaling, PI3K/AKT signaling, TGF-β signaling, EGF signaling, and pregnenolone biosynthesis. Identification of Biological Functions Altered by FGF9 Treatment The IPA identified 500 annotated biological functions for the differentially expressed transcripts altered by FGF9 in vitro treatment in bovine TC. The top ten identified biological functions predicted to be increased by FGF9 in TC are shown in Fig. 2 in order of activation z-scores (z-scores measure the correlation between relationship direction and gene 149 expression, but only z-scores greater than 2 or smaller than -2 are considered significant for predicted activation state). Because FGF9 has been reported to stimulate bovine TC proliferation at the same time that it suppresses steroidogenesis (Schreiber et al., 2012), special attention was given to functions related to cell fate, including cell proliferation, survival, differentiation, death, and apoptosis among the altered identified biological functions (Fig. 3). Nevertheless, although cell proliferation, survival, and differentiation functions all had a positive activation z-score, only cell proliferation and cell survival were predicted to be increased by FGF9 in TC (i.e., with z-scores greater than 2). Identification of Molecular Networks Affected by FGF9 Treatment Seeking to understand how molecules affected by FGF9 connect to each other and relate to specific functions, we analyzed the networks generated by IPA. The differentially expressed transcripts affected by FGF9 were categorized in 21 different networks. The top 10 networks according to p-score are shown in Fig. 4. In order to assess how FGF9 treatment may affect ovarian function, special attention was given to networks involving cell proliferation and steroidogenesis, two actions already reported to be affected by FGF9 in bovine TC (Schreiber et al., 2012). These networks are shown in Figs. 5 and 6, respectively. For cell proliferation, up-regulated (p < 0.05) transcripts were CCND1, FZD5, MYB, CASP3, FRMD4A, ACKR3, JADE2, RBPJ, HAUS8, ARRDC2, DENND2A, H2AFZ, while down-regulated (p < 0.05) transcripts were HLA-DRA, AARSD1, MLF1, JADE3, UBE2D4, PPP2R2B, NQO1, HMOX1, AGTR1, RNF150, SOD, KCNAB1. For steroidogenesis, up-regulated genes (p < 0.05) by FGF9 were: TFPI, VLDR, SLC38A2, ACSL4, PRKCA, ARG2, PER2 while down-regulated genes (p < 0.05) by FGF9 were: COL14A1, OGN, IGF2, SORT1, AGTR1, GPIIB-IIIA, CYP2C9, STAR, CYP11A1, SIRT3, RIMS1, ARID5B; frizzled molecules were either down-regulated (SRFP2, FZD2, FZD4) or up-regulated (FZD5). 150 5. Discussion FGF9 is a powerful mitogen that stimulates cell proliferation in many tissues and has been implicated in many types of cancer (Todo et al., 1998; Hendrix et al., 2006; Sun et al., 2015). In the ovary, FGF9 has been reported to stimulate proliferation of both GC and TC (Schreiber and Spicer, 2012; Schreiber et al., 2012). Hence, it is no surprise that, based on Z- activation scores, cell proliferation was the biological function most affected by FGF9 in the present analysis (Fig. 2), with 157 out of 346 differentially expressed transcripts related with this function. The fact that the gene encoding for cyclin D1 (CCND1), a protein required for progression of the G1 phase of the cell cycle (Baldin et al., 1993) that has been previously detected in proliferating murine TC, but not GC (Robker and Richards, 1998), was the most up-regulated transcript by FGF9 treatment in the present microarray further supports the importance of FGF9 in stimulating TC proliferation. In addition, two other genes among the top 20 up-regulated transcripts by FGF9 (FZD5 and MYB) are related to cell proliferation (as shown in Table 1 and Fig. 5). In fact, FZD5 encodes the protein Frizzled family receptor 5, a cell-surface receptor that interacts with Wnt proteins to stimulate cell proliferation of human endometrial adenocarcinoma cells (Carmon and Loose, 2008) and bovine TC (Spicer, 2016), while MYB (v-myb myeloblastosis viral oncogene homolog) encodes the protein c-Myb, a transcription factor that stimulates cell proliferation while suppressing apoptosis and differentiation of a variety of cell types, including human myeloid leukemia cells (Anfossi et al., 1989; Lyon et al., 1994) and human breast cancer cells (Drabsch et al., 2010). The protein c-Myb is a positive regulator of CCND1 in human liver cancer (Zhang et al., 2012) and breast carcinoma (Mitra et al., 2016) cells. Bartunek and colleagues (2002) reported that MYB and FGF2 cooperate to sustain avian hematopoietic cell proliferation while preventing them to differentiate into red blood cells. Hence, FGF9 appears to be stimulating the progression of the G1 phase of the cell cycle for bovine TC proliferation through the Wnt signaling pathway and the regulation of CCND1. Interestingly, WNT3A, a member of the Wnt family of ligands 151 has been reported to increase FGF9 mRNA abundance in bovine TC (Schreiber et al., 2012), reinforcing the association between FGF9 and the Wnt signaling pathway. Another intriguing observation from the cell proliferation Network generated by IPA (Fig. 5) is the fact that transcripts for caspase-3 (CASP3) were increased in TC in response to FGF9. Indeed, although CASP3 is a major downstream effector of apoptosis in GC of atretic follicles, CASP3 immunostaining has also been reported in TC of healthy follicles (Boone and Tsang, 1998). Reports imply that CASP3 may be involved in selective destruction of organelles and may be enhancing cell survival and proliferation in certain situations (Perfettini and Kroemer, 2003; Kuranaga, 2011). Interestingly, CASP3 cleaves the cyclin- dependent kinase inhibitor 1B (p27Kip1), a mammalian regulator of the cell cycle that induces G1 arrest, thus stimulating lymphoid cell proliferation (Frost et al., 2001). Because p27Kip1 decreases during TC proliferation and increases during TC terminal differentiation (Robker and Richards, 1998), the present data indicate that, like with lymphoid cells, CASP3 may be stimulating bovine TC proliferation by preventing p27Kip1 to arrest cells at G1. A lack of change in p27Kip1 mRNA following FGF9 treatment supports a post-transcriptional regulation of p27Kip1. Furthermore, MIR221, one of the top up-regulated genes in the present study, has been reported to down-regulate p27Kip1, via prevention of translation, in human hepatocellular carcinoma (Fornari et al., 2008). It is also noteworthy that the genes HMOX1 and NQO1 were down-regulated by FGF9, as shown in the cell proliferation Network (Fig. 5). These genes are antioxidant and cytoprotective, being activated by the transcription activator NRF2 in response to oxidative stress in order to protect the cells (Attucks et al., 2014). Not by coincidence, NRF2-mediated oxidative stress response is among the top canonical pathways affected by FGF9 in the present study (Fig. 1). Reactive oxygen species (ROS) are constantly produced during metabolic processes and it is now well accepted that ROS at high concentrations are cytotoxic, but, at moderate concentrations, ROS play a role in signal transduction processes, including cell proliferation (Hu et al., 2005; Zhang et al., 2016). In the ovary, high levels of 152 ROS have been shown to stimulate the initiation of apoptosis in GC of antral follicles (Devine et al., 2012; Zhang et al., 2016). Nevertheless, in theca-interstitial cells, generation of ROS is required to maintain cell proliferation, and a reduction in the level of ROS inhibits cell proliferation (Duleba et al., 2004). Hence, the reduction in transcripts for HMOX1 and NQO1, factors that reduce ROS concentrations, by FGF9 observed in the present study suggests that ROS may be important for bovine TC proliferation. This idea is further supported by the fact that ROS mediate FGF2 biological effects in chondrocytes (as reviewed by Sainz et al., 2012). In addition, Cui and co-authors (2015) recently reported that NQO1 is frequently up-regulated in human ovarian carcinomas, supporting the idea that controlled regulation of NQO1 may play an important role in ovarian function. FGF9 has also been reported as a regulator of steroidogenesis by murine, bovine, and porcine follicular somatic cells (Drummond et al., 2007; Schreiber and Spicer, 2012; Schreiber et al., 2012; Evans et al., 2014). In bovine GC, FGF9 decreases IGF-1 plus FSH- induced E2, P4, and pregnenolone production while decreasing mRNA abundance for the steroidogenic enzyme CYP11A1 and for the FSH receptor (FSHR) of both small (1-5 mm) and large (8-22 mm) antral follicles (Schreiber and Spicer, 2012). In bovine TC, FGF9 decreases IGF-1 plus LH-induced P4 and androstenedione (A4) production while decreasing mRNA abundance for the steroidogenic enzymes CYP11A1 and CYP17A1 and for the LH receptor (LHCGR) of large antral follicles (Schreiber et al., 2012). Therefore, the fact that CYP11A1 is among the top down-regulated genes is not surprising (Table 2). In addition, other genes related to steroidogenesis of TC were down-regulated by FGF9 in this study (Fig. 6), including the genes encoding for steroidogenic acute regulatory protein (STAR), insulin- like growth factor 2 (IGF2), angiotensin II receptor, type I (AGTR1), frizzled class receptor 4 (FZD4), and cytochrome P450, family 2, subfamily C, polypeptide 9 (CYP2C9). STAR is responsible for mediating the transport of cholesterol to mitochondria (Lin et al., 1995); IGF2, AGTR1 and FZD4 appear to be important to P4 production, since both IGF2 (Spicer et al., 2004) and angiotensin II (Acosta et al., 1999) have been reported to stimulate P4 release 153 while FZD4 knockout mice have lower P4 production (Hsieh et al., 2005); CYP2C9 is involved in catabolism of P4 (Yamazaki and Shimada, 1997). Hence, these observations suggest that FGF9 affects several genes that may act in concert to suppress P4 and A4 production by bovine TC. The fact that STAR was down-regulated in this study is in contrast to a previous report by our group in FGF9-treated TC and requires further investigation (Schreiber et al., 2012). Finally, the observation that the frizzled proteins encoding genes FZD2, FZD4, and SRFP2 were down-regulated in the steroidogenesis Network suggests that these genes can be also linking the Wnt signaling pathway with steroidogenesis in TC, but this hypothesis also requires further investigation. Recent studies support this idea by showing that WNT5A increases androstenedione production by bovine TC (Spicer, 2016). Steroidogenesis by TC and GC of large antral follicles is crucial for follicular differentiation (Knecht et al., 1984; Evans and Fortune, 1997; McGee and Hsueh, 2000; Young and McNeilly, 2010). Since FGF9 decreases synthesis of P4 and A4 and reduces mRNA abundance for both LHCGR and CYP17A1 (Schreiber et al., 2012), critical factors for TC differentiation in preovulatory follicles (Richards, 1994; McGee and Hsueh, 2000), it seems likely to suppose that FGF9 acts as an anti-differentiation factor of TC of large antral follicles, at least in cattle. This idea is further reinforced by the observation that abundance of bovine FGF9 mRNA is greater in TC of all sizes of E2-inactive follicles (i.e., future atretic follicles) than in large E2-active follicles (i.e., dominant follicles) at an early growing phase of the first dominant follicle (Schütz et al., 2016). Thus, the fact that FGF9 up-regulated CCND1 and MYB, factors that suppress cell differentiation while stimulating cell proliferation (Lyon et al., 1994; Robker and Richards, 1998), together with the observation that FGF9 was not predicted to increase TC differentiation (Fig. 3) in the current study corroborates the idea that FGF9 is stimulating bovine TC proliferation rather than differentiation. In summary, the current microarray study allowed the identification of 345 differentially expressed transcripts in bovine TC following in vitro FGF9 treatment, several of them related to cell proliferation, survival, and steroidogenesis. The data presented herein 154 provide an interesting picture of how FGF9 promotes TC proliferation while suppressing cell differentiation. The investigation of the candidate genes and pathways unraveled here by IPA will not only provide an insight of how FGF9 plays a role in folliculogenesis in cattle, but will also help to unveil how this growth factor affects pathological conditions such as cystic ovarian follicles and ovarian cancer. Acknowledgements The authors thank the assistance of Dr. E.-S. Han and Jacob Crowley at the University of Tulsa Microarray Core Facility for microarray assistance; Creekstone Farms (Arkansas City, KS) for donation of bovine ovaries; the Oklahoma State University Recombinant DNA/Protein Core Facility for use of their equipment. 155 Table 1. 20 most up-regulated genes by FGF9 treatment in bovine TC. Probe set Gene symbol Gene Name Fold P-value change 1 Bt.16538.2.A1_at CCND1 Cyclin D1 4.96 0.0000569 2 Bt.12927.1.S1_at HAS2 hyaluronan synthase 3.90 0.000803649 2 3 Bt.1817.1.S1_at ETV1 Ets variant 1 3.49 0.00142088 4 Bt.996.1.S1_at --- transcribed locus 3.25 0.00080151 5 Bt.19826.1.A1_at --- transcribed locus 3.23 0.0210203 6 Bt.6983.1.S1_at SOX9 SRY (Sex 3.16 0.0377339 determining region Y)-box 9 7 Bt.29956.1.A1_at BMP2 bone morphogenetic 2.98 0.00193277 protein 2 8 Bt.10212.1.S1_at PHLDA1 Pleckstrin 2.97 0.000000737 homology-like domain, family A, member 1 9 Bt.3051.1.S1_at --- Transcribed locus 2.92 0.0000611 10 Bt.72.1.S1_at MMP1 matrix 2.90 0.00506371 metallopeptidase 1 (interstitial collagenase) 11 Bt.16100.1.S1_at FZD5 Frizzled family 2.81 0.000317748 receptor 5 12 Bt.303.1.S1_at P2RY1 purinergic receptor 2.74 0.0194217 P2Y, G-protein coupled, 1 13 Bt.13073.1.S1_at SERPINB2 serpin peptidase 2.63 0.0182733 inhibitor, clade B (ovalbumin), member 2 14 Bt.568.1.S1_at IBSP integrin-binding 2.52 0.0337404 sialoprotein 15 Bt.10648.1.S1_at RRM2 ribonucleotide 2.43 0.0240124 reductase M2 16 Bt.11109.1.S1_at MIR221 microRNA mir-221 2.43 0.0000000273 17 Bt.12781.1.S1_at MYB v-myb 2.40 0.0397893 myeloblastosis viral oncogene homolog (avian) 18 Bt.17951.1.A1_at --- Transcribed locus 2.36 0.0257273 19 Bt.5618.1.A1_at CNTNAP2 contactin associated 2.33 0.000372504 protein-like 2 20 Bt.20507.1.S1_at CYP26B1 cytochrome P450, 2.31 0.00301863 family 26, subfamily B, polypeptide 1 156 Table 2. 20 most down-regulated genes by FGF9 treatment in bovine TC. Probe set Gene Gene Name Fold P-value symbol change 1 Bt.4939.1.S1_at SFRP2 secreted frizzled-related -4.09 0.00392234 protein 2 2 Bt.7190.1.S1_at CYP11A1 cytochrome P450, -4.09 0.0236564 family 11, subfamily A, polypeptide 1 3 Bt.13482.1.S1_at NOV nephroblastoma -3.25 0.0116386 overexpressed 4 Bt.13855.2.S1_at ADAMDEC1 ADAM-like, decysin 1 -3.25 0.00490709 5 Bt.11656.1.S1_at CGN cingulin -3.06 0.000463423 6 Bt.19661.1.S1_at PPP2R2B protein phosphatase 2, -3.01 0.000310913 regulatory subunit B, beta 7 Bt.20574.1.S1_at AQP11 aquaporin 11 -2.99 0.00102593 8 Bt.10021.1.S1_at MYL7 myosin, light chain 7, -2.72 0.0261566 regulatory 9 Bt.19322.1.A1_at COL4A6 collagen, type IV, alpha -2.69 0.0213395 6 10 Bt.5341.1.S1_at OGN osteoglycin -2.68 0.00729922 11 Bt.23113.1.A1_at --- transcribed locus -2.66 0.0000184 12 Bt.22768.1.A1_at SVEP1 sushi, von Willebrand -2.65 0.0126702 factor type A, EGF and pentraxin domain containing 1 13 Bt.24211.1.A1_at ASPN asporin -2.61 0.00459269 14 Bt.1745.1.S1_at KRT18 keratin 18 -2.59 0.00608511 15 Bt.7042.1.S1_at NPVF neuropeptide VF -2.58 0.00210952 precursor 16 Bt.16495.1.A1_at COL4A5 collagen, type IV, alpha -2.56 0.0140642 5 17 Bt.5530.1.S1_at DHRS3 dehydrogenase/reductase -2.49 0.00124302 (SDR family) member 3 18 Bt.27645.1.A1_at ISM1 isthmin 1 homolog -2.46 0.00446444 (zebrafish) 19 Bt.3885.4.S1_X_at CLCA3P chloride channel -2.36 0.00487499 accessory 3 (pseudogene) 20 Bt.12685.1.S1_at MYH11 myosin, heavy chain 11, -2.30 0.0294988 smooth muscle 157 Fig. 1. Top 10 canonical pathways altered by FGF9 in bovine TC identified by IPA. Numbers to the right on the bars indicate the number of differentially expressed transcripts in each pathway. - - 158 Fig. 2. Top 10 biological functions for the differentially expressed transcripts altered by FGF9 treatment in bovine TC identified by IPA. Numbers to the right on the bars indicate the number of differentially expressed transcripts in each pathway. 159 Fig. 3. Biological functions related to cell fate altered by FGF9 in bovine TC identified by IPA. Among these functions, based on activation z-score, only proliferation of cell and cell survival were predicted to be significantly increased in response to FGF9 in TC. The numbers on the top of each bar indicate the number of differentially expressed transcripts in each pathway. 160 Fig. 4. Top 10 networks generated by IPA according to score. The greater the area in the graph, the higher the score of the network. 161 Fig. 5. Network of differentially expressed transcripts related to cellular growth and proliferation (Network 3). The bold lines show a direct association among molecules while dashed lines show an indirect association among the molecules. Different shapes of molecules indicate different functions. Significantly up-regulated genes (p < 0.05) by FGF9 in this network were: CCND1, FZD5, MYB, CASP3, FRMD4A, ACKR3, JADE2, RBPJ, HAUS8, ARRDC2, DENND2A, H2AFZ; significantly down-regulated genes (p < 0.05) by FGF9 in this network were: HLA-DRA, AARSD1, MLF1, JADE3, UBE2D4, PPP2R2B, NQO1, HMOX1, AGTR1, RNF150, SOD, KCNAB1. 162 Fig. 6. Network of differentially expressed transcripts related to steroidogenesis (Network 15: Lipid metabolism, molecular transport, small molecule biochemistry). The bold lines show a direct association among molecules while dashed lines show an indirect association among the molecules. Different shapes of molecules indicate different functions. 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Up-regulation of fibroblast growth factor (FGF) 9 expression and FGF-WNT/beta-catenin signaling in laser-induced wound healing. Wound Repair Regen. 22: 660-665. 172 CHAPTER VI SUMMARY AND CONCLUSION Several factors produced by the ovarian follicular somatic cells, granulosa (GC) and theca cells (TC), are known to regulate follicular development, including the fibroblast growth factors (FGFs). Among these, FGF9 has been characterized as an anti-differentiation factor of bovine follicles, stimulating both GC and TC proliferation while suppressing hormone-stimulated steroidogenesis. Nevertheless, whether production of FGF9 by ovarian follicular cells changes during folliculogenesis is unknown. Therefore, we investigated changes in FGF9 mRNA abundance in bovine GC and TC during development of first dominant follicle. Our findings reinforce the idea that FGF9 is acting as an anti-differentiation factor, since its mRNA abundance was greater in subordinate than in large dominant follicles. In addition, seeking to have a comprehensive view of the role of FGFs in folliculogenesis, we investigated how transcripts for selected FGF receptors (FGFR1c, FGFR2c, FGFR3c, and FGFR4) change in GC and TC during development of the first dominant follicle of cattle. We found that mRNA for these FGFRs are also greater in subordinate than in large dominant follicles, suggesting that, similar to FGF9, FGFRs may contribute to follicular selection in cattle. Finally, we investigated how FGF9 affects biological functions of TC through the use of microarray technology and bioinformatics tools such as Ingenuity Pathway Analysis. We were able to identify pathways and novel genes affected by FGF9 that are involved in 173 steroidogenesis, cell proliferation, and survival. Taken together, these findings support the idea that FGF9 regulates selection of the dominant follicle in cattle. Possible applications of this research include using FGF9 in protocols of superovulation and the manipulation of follicular waves in cattle in order to improve reproductive efficiency. Furthermore, genes and pathways unveiled by microarray could be targeted in research for therapy of ovarian cancer caused by dysregulated FGF9 signaling. 174 VITA LUIS FERNANDO SCHUTZ Candidate for the Degree of Doctor of Philosophy Dissertation: EXPRESSION AND ROLE OF FIBROBLAST GROWTH FACTOR 9 (FGF9) IN BOVINE FOLLICULOGENESIS Major Field: Animal Science Biographical: Education: Completed the requirements for the Doctor of Philosophy in Animal Science at Oklahoma State University, Stillwater, Oklahoma in July, 2016. Completed the requirements for the Master of Science in Animal Science at Santa Catarina State University (UDSEC), Lages, Brazil in 2012. Completed the requirements for the Doctor of Veterinary Medicine at Federal University of Rio Grande do Sul (UFRGS), Brazil, 2007. Experience: Research Experience Master’s Research Laboratory of molecular and developmental biology, University of Fortaleza (UNIFOR), Brazil, March 2011 to August 2011. Student Research Assistant Embryology and biothecnology of reproduction laboratory, School of Veterinary Medicine, UFRGS, Brazil, April 2002 to April 2004. Teaching Experience: Teaching Assistant, Introduction to Animal Science (ANSI 1124), Agricultural Animals of the World (ANSI 3903), Dairy Cattle Science (ANSI 4543), Animal Reproduction (ANSI 3443), Oklahoma State University, Spring semester, from January 2013 to May 2013, from January to May 2014, and from January to December 2015. Professional Memberships: American Dairy Science Association International Embryo Transfer Society